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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.
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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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HanByul P
Hi Jing Wu, Just a quick question: Why is this algo waiting for a month and starting to run from a second month? Is it for warming up? Can we modify this algorithm to run from the first month? Just remove the flags? Please let me know. Thank you.
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Weiheng Liang
Thank Jing.
market cap = Shares Outstanding * Price = Shares Outstanding * (Earnings Per Share * PE ratio)
That's what I was waiting for. It's a huge improvement for my algo.
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Xi Liu
Hi Jing Wu,
1. I ran the Algo, and found the exit function(when current SPY price is lower than last N-day moving average price, then liquidate all the open positions and buy TLT.) doesn't work all the time. The exit function doesn't work, making it performs bad on crisis.
The momentum strategy has relatively higher volitility. I think one of the drawback of momentum strategy is failing to act quickly to close a bad position. I'm considering to add a Stop Market Order of the portfolio composite seperately. However, I'm new to do an alogo with python, after reading the Documentation and browing the internet, I only learned how to add StopMarket order while making market order, like this:
self.MarketOrder(self.baba, 300)
self._stopMarketTicket = self.StopMarketOrder(self.baba, -300, slice['BABA'].Close * Decimal(0.95), "stop market")
This algo's code seems complex to me, I can't find the place to get the price and deploy the StopMarket order.
Can you give me some instructions on this problem?
2. I want to test the algo with leverage, for example, 1.5 leverage then I modify LINE 96:
weight = 0.99/len(chosen_df)
for symbol in chosen_df.index:
self.AddEquity(symbol)
self.SetHoldings(symbol, weight)
I change 0.99 to 1.5, but it doesn't work. Do you know how to set the weight here?
Thank you a lot.
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Jon Quant
I have sprinkled a bunch of debug lines in the code just to analyze the behavior and I have noticed that if I set the following dates:
SetStartDate(2004, 1, 1); SetEndDate(2004, 4, 1);...the value for the "symbols" variable in "FineSelectionFunction" gets assigned on 01/03/2004 only to be used by the "rebalance" function a month later, 02/02/2004. This tells me that the rebalance is operating on a fine "symbols" list that is a month old. Is this intentional?
One other behavior that I have noticed is that the "CoarseSelectionFunction" and "FineSelectionFunction" never gets called on the "MonthStart" day. In my example date window, it never gets called on 01/02/2004. Is the "MonthStart" schedule somehow interfering with the Coarse and Fine events?
Thanks!
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Jing Wu
Hi Xi Liu,
You can use self.StopMarketOrder() everywhere in your algortihm. For the stop price, you can use
"self.Securities["BABA"].Close" * Decimal(0.95) instead of "slice['BABA'].Close * Decimal(0.95)" because you can only get the slice data in OnData() method.
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.
HanByul P
Hi Jing Wu, I cloned your new method (for Market Cap) algo and ran for 2015 to March 1st of 2018. I found that the leverage went up to 500% (5x) in the early 2016 and came down to 300% (3x) in the end of this backtest period. You set the maximum weight to 0.99x as below. I guess something should be fixed. Can you take a look and fix the leverage control (e.g. maximum 2.0x)? Thank you.
weight = 0.99/len(chosen_df)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.
Ton86
Hi Jing Wu,
I ran this today 4/2/2018 and was looking for the trade signals to occur by 10am PST since that seems to be the time the trades occur in the backtesting. Do we need to wait until end of first day of the month or should the signals be there by 10am PST, or another time?
When setting this up for trading live what types of alterations might need to be made? Is there a page/link that describes this or is this something support helps with after creating a live account?
Thank you!
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Ton86
Jing Wu,
Also seeing errors like this:
Backtest Handled Error: The order quantity for TLT cannot be calculated: the price of the security is zero.Doesn't look like April 2018 TLT trade is getting executed because of it. Could it be that the algo is looking at the first of the month for the price but isn't seeing it because the first falls on a weekend?
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Yulong Jiang
Hi, Jing, I am new to QuantConnect so a little confused on your code.
it seems that you do everything on Intialize() and pass on OnData(), does it mean Initialize() will run many times instead of just setting the initialial condition?
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Michael Manus
nope only once
everything?? settings holdings are in rebalance ....
check the bootcamp(-tab) in the algorithm lab
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Wei Chian Ong
I'm a little bit confused by the code snippet below. We check the moving average exit gate, and if it shuts, we loop through each position, if it's not TLT (bonds), then we exit the position. That makes sense.
if self.Securities[self.spy].Price < spy_hist.mean(): for symbol in self.Portfolio.Keys: if symbol.Value != "TLT": self.Liquidate()But, when we use self.Liquidate() and don't specify a security, doesn't it just liquidate every single position in the portfolio? Why bother to loop through the Portfolio keys at all, if we are just going to liquidate everything anyway? In my head it seems that self.Liquidate(symbol) or self.Liquidate(symbol.Value) would make more sense. Can someone tell me what I am missing?
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Weiheng Liang
Wei Chian Ong, what the code Liquidate() will do is possibly more tricky than you imagined. I suggest you check the code inside ideally debug carefully by using VS.
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Wei Chian Ong
Thanks for the reply. I've had a look at your previous post regarding the self.Liquidate() method, and my question probably doesn't run as deep as the intricacies of dark pools and slippage in actual trading. It's more of a question regarding the coding itself. The documentation and this forum post and reply seem to indicate that using self.Liquidate() without a security specified, will liquidate all positions, and I was having trouble understanding why we bother looping through each symbol in the portfolio and checking if it's not treasury bond ETF, if we go ahead and liquidate everything anyway, would it not make more sense to use self.Liquidate() with the actual position we are currently looping through?
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Weiheng Liang
I was not meaning dark pools. I was just saying we should look inside the detail codes of Liquidate() in VS if there is something confused.
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Wei Chian Ong
I'm not familiar with how to use visual studio (I assume that's what VS stands for), so I'll have to try it using log or debug calls.
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Nick Jensen
I cloned this algorithm and received an error "Invalid Token" on the self.SetStartDate function, so am unable to run or backtest. Is anyone receiving this same error? Is there an easy fix?
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Wei Chian Ong
I think I kept getting the same Nick and I wasn't sure why either. I deleted the code for the self.SetStartDate and self.SetEndDate and then re-typed them manually in case it was a whitespace issue or something (probably a very inefficient way to do that anyway). Same problem, but I repeated that several times and eventually it worked. Not a very scientific response to your question .......
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.
Jared Broad
The invalid token is from python 2.7 to python 3.6 upgrade. Since python 3.6 numbers can't be prefixed with 0 -- e.g. "01"
If you cloned an old backtest it can have dates with 2001, 01, 01 etc.
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Leng Dieb
I am trying the codes for the test on paper live server but it does not seem to generate any trade. Could you please advise anything need to be changed to run live for the paper 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.
Tocht
Any updates?
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