Here's an algo that buys the biggest loser with a slowing descent. I've used my Universe Template.
There's no slippage modelling but the algo only considers the 10 most liquid stocks and is of Daily resolution so slippage shoudn't completely destroy the alpha.
Market dynamics over the last five years seem favorable to this approach.
Michael Manus
Thank you for that algo. very interesting.
some thoughts:
someone on quantopian writes the following:
""This is my first time interacting with algo-trading so my first thought was to try something I thought other people would ignore, instead of using the top/bottom 10% of stocks I made that very small and it returned 20%. The smaller I made the value, the higher the return would get.""
taking maybe 5 different (higher/lower) stocks would give better results.
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Petter Hansson
This is pretty neat. Still waiting for backtest to finish but I think you're onto something good here. I will report back later.
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Michael Manus
ok bad comment above.....i mean not taking always the top/lowest 10....
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Petter Hansson
Some initial comments, I realize most things I mention are due to this algo being a protype:
- I couldn't see reasons for the last peak as I got out of memory on backtest, but beware there are exotic ETFs being traded by the algo right now (e.g. saw it trading VXX). One might wish to disallow it from trading these instruments that have special considerations.
- Slippage is indeed evil and even daily can ruin some good alpha. Would be worthwhile looking into how large it is on average here, even though for some ETFs it's almost completely neglible for daily bars (e.g. SPY, IWM).
- As far as I've read elsewhere, we're currently in a mode of market where a few big companies are driving it by outperforming the wider index. This might be contributing to the alpha? Saw the algo trading a lot of FANGs for instance.
- While beta isn't super high I'm still afraid of what happens on bad days. :-) 2015 stands out in the test period, but there will probably be worse due to correlations during tail events. However, I guess it's an acceptable risk compared to say being 100% long XIV, haha.
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Warren Harding
Another thing that should be mentioned is that there is no position building code, it just buys/sells with a single order in a simplistic fashion. For large accounts you would definitely want to spread the buys/sells out over time to avoid excessive slippage. As Petter mentioned it should be treated as a prototype, I'ld go over it carefully before trading it live.
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Anthony B
Beautiful...
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Vidal boreal
I just cloned and re-run it but similar result could not be reproduced. Lower sharpe and return. What is the reason?
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Daniel Chen
Hi KY,
Thank you for your question. The original algorithm in this post was done about 2 years ago. From then on, we fixed some data issues, so the data now is not exactly the same as the data two years ago, which leads to the difference.
We recommend you run this algorithm in the current LEAN engine with the most updated data. Thank you!
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Warren Harding
Interesting. I posted this in 2017 and forgot about it. I just cloned and ran it. It did quite well over the last two years out of sample.
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SherpaTrader
Does this need to have some setwarmup done, before it can be run for live. since it uses 3 days of historical data, ?
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Derek Melchin
Hi SherpaTrader,
This algorithm calls the History method inside OnData. This is not a practice we recommend as it slows down the execution speed. In regards to the question above, adding SetWarmup would not benefit this implementation since the History call is made during every OnData iteration. Instead, I'd recommend replacing the History call with some consolidators to automatically update the StockData properties.
Best,
Derek Melchin
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Simone Pantaleoni
Apologies :P Tagged the wrong Frank and cannot amend it now unfortunately :) anyway, better a compliment more, than one less isn't it? :P
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Frank Giardina
From the comments above from Frank Schikarski about using the High Yield Spread, attached is I think the FRED alternative dataset he is talking about. If someone can confirm that would be great. I did not see another dataset that fit the description
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Vladimir
Simone Pantaleoni,
Try this one
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Vladimir
Simone Pantaleoni,
Here is a backtest for OECD/KEI_LOLITOAA_KOR_ST_M from my June 2021 research.
I'd better chat with you in this thread.
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Vladimir
Simone Pantaleoni,
Here is a backtest for OECD "OECD/KEI_LOLITOAA_JPN_ST_M" from my June 2021 research.
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Frank Giardina
This is a work in progress. I cloned one of Vlad's earlier versions. I really like this algo for a macro view of investing. This version can probably be done in less code, average python coder here. I wanted to see what the economic stage/cycles have been since 2012 based on the kei strategy and then see how different ETFs performed in that cycle. I wanted to make it flexible enough to add and remove ETFs . Next i wanted to output the results to a comma separated log file so i could import to excel to see which ETFs performed the best. Any feedback / improvements greatly appreciated. One issue i am trying to fix is to add the number of days that a stage lasted, can't seem to get the python date functions to work (probably me)
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Simone Pantaleoni
Frank Giardina Thanks for joining the Team Frank! :)
I've created different versions of this strategy - the one below is what I'm using live:
PSR and DD are the best parts of this strategy in my opinion :)
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Frank Giardina
Very impressive, if anyone wants to conference call or collaborate and kick around some ideas, always up for that. I plan on looking at my results and trying some different approaches. Especially in the area of sub stages within the stage and how to speed the indicator. I also want to start using this in 2022
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JSO 2045
Hi guys. I'm pretty new to this so apologies for not having that much in the way of useful contribution to this conversation. Has anyone found a way to alleviate/offset 2022's downturn for this strategy (and a lot of others), or is the freakish nature of what's happened not something that can be effectively accounted for? Main reason for asking is that the low drawdown/volatiltiy of this strategy seemed like a big strength but has obviously taken a hit this year
All I can think of would be adding small hedges against each of the orders made by the algo in each of its “stages.” I will give it a try but am keen to hear what other peoples' thoughts are :)
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Frank Giardina
Not sure what to add , but there is another OECD dataset from the Federal Reserve site FRED https://fred.stlouisfed.org/ called USALOLITONOSTSAM. My understanding is this dataset is US only as opposed to the QUANDL dataset used in the algo. I have not been able to figure out how to get Quantconnect to use this data set instead. If i could figure out how to use that one instead I would. The two datasets are 90% correlated. In the meantime I am using a python notebook in Google colab to do the analysis. The Quandl indicator has indicated we are in a decline since April the FRED indicator says since March. I have noticed that with the FRED data they do go back and adjust the data so that does throw things off at times. If there is an interest in the notebook let me know and i will copy it in the post.
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Simone Pantaleoni
Hi Frank and JSO,The one you've picked, as you said, is US-only leading indicators - there're plenty available indeed (roughly one per country), but I would suggest to use the oecd or the world oneIn order instead to limit drawdown during 2022, just switch to cash (or “BIL” or “SHV”) when the TLT correlation to SPY is positive.Enjoy it
ps. if you like my comment, drop me some points/likes ;)
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Simone Pantaleoni
Just forgot to mention - I'm always open to collaborations - I'm available on Telegram or Discord (but I would prefer the first one, since I'm not a very heavy Discord user) :)
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JSO 2045
Simone Pantaleoni I like that idea of using the correlation, will try to give it a go. Finding a valid solution to this specific problem would help loads of strategies in the forums as well as this one. Could potentially even have a list of traditional hedges against the stock market and select the one with the lowest correlation across the last month (or something like that)
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Peter Guenther
Great job again, Simone Pantaleoni and Strongs, for getting this discussion started!
Sorry, time resources have been a bit tight. Anyway, I am currently musing about whether this could be used to trade FX pairs. The OECD data gives you international information about the comparative strengths of various economies. You got your interest rates, GDP growth, inflation figures, unemployment rates and so on, Based on this, one might be able to bet on one currency vs the other and/or to validate or refute existing trends in currency pairs. Hopefully, I can put something together over the next few weeks for the major currency pairs.
The time lag of the data (up to one month?) could be an issue for live trading – to what extent could be tested by simulating lagged data usage. If it is a substantive issue, the question will be whether more up-to-date datasets could be identified, such as by getting the data directly from the national bureaus of statistics or similar.
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Simone Pantaleoni
Hi Peter Guenther
Well spotted: publication delay can affect live performances, so to avoid so I've been “reading” the KEI value on the 15th of each month, basically taking into account the publication date instead of the “validity” date
About the FX Pair, that is actually another great idea, and should be rather easy to realize, even tough I would be curious to see if that is able to generate alpha since carry trade is also “a thing” - perhaps a better idea would be to pair trade Country-ETFs based on the related KEI strength
ps. Still need to get in touch with you privately Peter - how can I reach out 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.
Peter Guenther
That's great, Simone Pantaleoni. I will definitely share as soon as I've got a first version of the FX algo.
My contact:
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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