Hello,
I am trying to implement a strategy that goes long on 10 stocks with the highest ROC from the previous day and equally weighted buys into them and then liquidates all stocks at the end of that day. This would also include a stop loss of 2% for any of those stocks. This then repeats every day, know that during backtest universe runs at midnight.
Couple of issues that I am having with this:
1. For some reason on certain days it goes long on all the stocks at 9:31 am then sells a select amount of particular stocks at 9:32 am (not the whole security amount held), I am unable to figure out why it is selling and not even selling all the stocks held?
2. I don't think the Risk Management is working as it should, as the largest loss for a given day should only be a max of 2% (with a margin of error) if all of the 10 stocks have decreased more than 2% that day. I can't figure out why it won't sell throughout the day.
3. How do you have the universe scan through stocks not only on the NYSE but also the TSX and any other major stock exchange in North America?
I have been going over examples from GitHub to learn how to connect all the different classes like Selection, Alpha, Risk Management, Portfolio, etc. to try and learn the Universe Selection (I find the documentation a bit light compared to the rest of Quantconnects documentation, and the Bootcamp examples don't touch on connecting all the different classes) Please point me in the right direction for documentation on this area of Quantconnect with Universe Select.
https://github.com/QuantConnect/Lean/tree/5d762d16b2ec7bd48fd766b772b0921862deda22/Algorithm.FrameworkI found Emilio's forum from 2018 that was asking a very similar question, but even with that detailed forum, I am still struggling to answer all my questions.
https://www.quantconnect.com/forum/discussion/4665/managing-universe-and-trades-within-algorithm-framework/p1Any help to figure out these couple of issues would be fantastic.
Tate Linzel
I was able to figure out the problem to my first two questions which were both related to the Risk Management, there was no problem but that the stocks would hit their stop loss and sell. The stocks would drop quickly in the morning and be sold the minute after they were bought.
New questions that I have as I progress the algorithm:
1. How do you limit the numbers of times a stock can consecutively be in the portfolio of securities? I would like to limit this to a max of 2 days in a row.
2. Is it possible to reallocate a stock's portfolio to another stock partway through the day? For example, I have noticed that some stock's prices won't move throughout the day, therefore have a rule if the price hasn't moved in 1 hour, then liquidate the stock and reallocate that cash to another stock currently in the portfolio that has the highest intraday PNL. Or if a stock hit it's stop loss then do the same, sell, and reallocate.
Thank you for your help.
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Derek Melchin
Hi Tate,
The universe selection model implemented above currently selects the securities that have the greatest ROC from the close 2 days ago to the close of the previous trading day, not from the previous close to the current day's open. Refer to this related thread regarding the latter.
> How do you have the universe scan through stocks not only on the NYSE but also the TSX and any other major stock exchange in North America?
We currently only support the major exchanges in the USA.
> Please point me in the right direction for documentation on this area of Quantconnect with Universe Select.
We recommend reviewing the documentation here. We are in the process of updating our documentation. We appreciate the feedback and patience in the mean time.
> How do you limit the numbers of times a stock can consecutively be in the portfolio of securities? I would like to limit this to a max of 2 days in a row.
We can limit the number of consecutive days we purchase the same security by tracking which securities we purchase each day. Then in our Update method, we include
days_purchased = [security.Symbol in symbols for time, symbols in self.symbols_by_time.items()] if days_purchased and all(days_purchased): continue
See the attached backtest for reference.
> Is it possible to reallocate a stock's portfolio to another stock partway through the day?
Yes, to accomplish this, we'd need to emit insights intraday when we want to rebalance the portfolio.
Best,
Derek Melchin
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Lars Klawitter
To Yuri's earlier point of there being a difference between backtests and live trading as to when the stop orders are placed:
I've been running the strategy (using a larger universe and shorter opening range as per my previous post) on IBKR paper trading (i.e. on an actual IBKR account, not via QC paper trading) and as Yuri suggested, the stop orders are at times placed within the same minute. Mostly 20-40 seconds after the entry:
in one case the stop order was placed the same instance as the entry:
I tried second resolution, but that seems impractical given the large universe size.
So this is my attempt at an artificially delayed stop order placement:
I'm not a C# coder, so I definitely don't know what I'm doing. Backtests with this code produce by and large comparable results with the original code, so I'll try paper trading next.
Would the above code change make sense to you?
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Yuri Lopukhov
So far I can see two issues:
I can't fix the first issue in C#, so I guess I will switch to Python version unless somebody else fixes the C# version and share it. Not sure if fixing it will improve results as well.
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Jack Pizza
define: “does really well with 1 minute” ….. 2000-2002 still utterly collapses fail to see well really well fits in….
or does really well when overfitting super hard?
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Quant Stratege
These backtests are not representative of live performance. When adding slippage, it can be significant at the open due to volatility, small-cap stocks, and using stop orders, making the results much less appealing.
Just add this line when adding securities:
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Lars Klawitter
You're right. I had previously only simulated very small constant slippages, but MarketImpactSlippage has quite a savage effect…
If it looks too good to be true…
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
AleNoc
I noticed a difference between the backtest and the selection with live data (data provider QuantConnect). What data provider do you use for live trading?
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Evan lightner
I don't know where to start, I'll have to write a whole post and how I'm planning to implement this strategy. But first of all thank you @derek for sharing this (and of course for everything you've done with QC -its been a game changer for me).
But first of all, I just want to comment with one simple non-coding question….
Why are a good amount of people HATING on this strategy? I understand the backtest cherry pick , but for a bare bones boiler plate ( i messed around with some variables like holdings and percent risk and still got good results) , this is the best algo I've seen in a while, especially for being shared so freely - not to mention brand new piece of research in the community.
Is there just some sort of deep skepticism in the quant community at large I guess, inherently? I suppose that fits!
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Kevin Patterson
Does anyone else end up with very different symbols when running the exact same algo in backtesting vs live (IBKR paper trading)? For example when it is set to choose 20 symbols, I'll see maybe only half overlap –- and of course the ones going positive for the day in the backtest are the ones not picked up live 😅. Seems the relative volume calculations aren't exactly the same and it doesn't take much to move the symbols you get. This is my first foray in to large universe algo's, is this type discrepancy common with large universe backtests or is there settings to help make it line up better with live? S
Some folks were asking about sized nodes: after trying the python version on IBKR (with a few mods) an L1-2 node will make it through one day (it crashes after close though, so likely you need the next level up if you dont want to restart daily)
Thanks for all the python related posts, even if I don't end up trading it, the algo has been super helpful for learning more about the QC code and had some good recipes in it that I think would be helpful for any algorithm.
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
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