Very interesting and once again congratulations for producing such clean and easy to understand code. First of all it looks like the indicator fails when the VIX goes super high but the the rest of the signals seem pretty decent. But it is probably difficult to determine (in real time) if the value of the VIX will continue to rise if the indicator is used.
Another great video. Another possible explanation for the lower mean returns in your test is that their one month moving average was probably 21 trading days (not 30 days),
Fantastic video. So much to absorb, I'm going to watch it again. At the beginning you're taking the rolling mean of the previous 30 days, but that's not a month, it's 6 weeks (plus many/most(?) 6 week periods would include a holiday). This probably wouldn't impact the number of entry signals, but it might shift the timing of the entry by a day or two (?), which might account for the slight difference to the JPM results?
Could I offer a different take? While the signal looks programmed as per the article, I believe JPM's instruction after that was to use the signal to buy the S&P 500. Since I am relatively new to Pandas , I was wondering how one could combined financial data of two tickers. Maybe the strat could be reasessed for 6month performance on the S&P when using the VIX signal
Love your work, but the risk is the model is optimised in specifying 50% deviation from vix mav, further you don't know when u are in a technical recession until after the event due to lag in gdp being released. How about using vix as input into random forest model to predict when to buy stocks?
could set up your algo bot to be triggered after this indicator has been met, then trade for the period of 6 months, knowing youll most likely out perform the market?
MA20 may fit better since Stock trading ist closed on the Weekend. Further it would bei nice too see the Signals in the chart. BUT once more thanks great video
Is playing with the core parameters a sensible strategy to improve the performance of these types of strategies? For example, changing the MA window to 10 days increases the mean return to around 10 percent. Does that make sense? Thanks again for the great video.
Amazing stuff! On a side note, would be interesting to test this strategy again in like 2 years. Chances are high all profits are getting wiped out but let’s see 😂
JPM has the caveat that the signal doesn't apply during a recession. Problem is you can't confirm a recession until two quarters (six months) at least.
Hi,it’s me again :) I have maybe an cool challenge. Try to generat a Elliot wave indicator. It uses some series of highs an lows. The challenge is to indicate every Elliot wave in a df.
Great video as it's very instructive. However, I think the signal itself is complete bollocks. But the great thing is you have shown us how to piece and parse the data together to think up and code our own signals to test. Thank you.
Couldn't you just grab the current price 6 months ahead and compare with the entry price? Not sure why we need the cumprod/accumulate all days in between. Cheers!
@@Algovibes by the way, have already showed in some other video how to use python to send real time orders mainly for stocks? Something like using the interactive brokers API or alpaca? I know you have done that for crypto using binance. Thanks for the great content!
Sure. I was just testing the strategy as described in the article. There is probably a lot of improvement potential. In general the strategist just wanted to show the good buying opportunity in those situations.
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Hey AlgoVibes. You come up with so nice videos. Really engrossing ones. Please keep coming up with more of such quality contents. God bless you
Thank you so much Rajeev and everyone who liked your comment. Appreciate your kind words!
Very interesting and once again congratulations for producing such clean and easy to understand code. First of all it looks like the indicator fails when the VIX goes super high but the the rest of the signals seem pretty decent. But it is probably difficult to determine (in real time) if the value of the VIX will continue to rise if the indicator is used.
Thanks man. Yeah, that's a good observation indeed.
Another great video. Another possible explanation for the lower mean returns in your test is that their one month moving average was probably 21 trading days (not 30 days),
Thanks a lot Victor. Good point!
Amazing content as always! Would love to see Low Volatility portfolio construction and its alpha generation, etc.
Thanks a lot man :-)
THANK YOU ALGOVIBES
WELCOME justcARS 😛
Fantastic video. So much to absorb, I'm going to watch it again. At the beginning you're taking the rolling mean of the previous 30 days, but that's not a month, it's 6 weeks (plus many/most(?) 6 week periods would include a holiday). This probably wouldn't impact the number of entry signals, but it might shift the timing of the entry by a day or two (?), which might account for the slight difference to the JPM results?
Thanks a lot mate. That's a good observation and should explain some of the minor differences indeed.
just wonderful, thank you
Thanks a lot Pavel!
Amazing content, keep it up please.
Thank you very much mate
Thanks for sharing. Always nice videos
Thx rraul :-)
Could I offer a different take?
While the signal looks programmed as per the article, I believe JPM's instruction after that was to use the signal to buy the S&P 500.
Since I am relatively new to Pandas , I was wondering how one could combined financial data of two tickers. Maybe the strat could be reasessed for 6month performance on the S&P when using the VIX signal
Hi Andre, sure!
Be invited to check out my Python for Finance playlist. I am using 1.000s of tickers in one dataframe and trading strategy.
Love your work, but the risk is the model is optimised in specifying 50% deviation from vix mav, further you don't know when u are in a technical recession until after the event due to lag in gdp being released. How about using vix as input into random forest model to predict when to buy stocks?
Thanks a lot man. Yea that's a valid point.
Great video
Thanks a lot buddy
This was very interesting!! Useful? Not so much, but very interesting
could set up your algo bot to be triggered after this indicator has been met, then trade for the period of 6 months, knowing youll most likely out perform the market?
MA20 may fit better since Stock trading ist closed on the Weekend.
Further it would bei nice too see the Signals in the chart.
BUT once more thanks great video
Thanks my man!
Is playing with the core parameters a sensible strategy to improve the performance of these types of strategies? For example, changing the MA window to 10 days increases the mean return to around 10 percent. Does that make sense? Thanks again for the great video.
Make sense, yes! Thanks a lot for watching and sharing your thoughts.
Yes really nice video one can learn a lot
Thanks a lot Prashant
Bro you are the best
Thank you my friend!
Amazing stuff! On a side note, would be interesting to test this strategy again in like 2 years. Chances are high all profits are getting wiped out but let’s see 😂
Thanks mate, Let's see about your claim 😛
JPM has the caveat that the signal doesn't apply during a recession. Problem is you can't confirm a recession until two quarters (six months) at least.
this is cool, thx a lot
Thx for watching :-)
Hi,it’s me again :)
I have maybe an cool challenge.
Try to generat a Elliot wave indicator. It uses some series of highs an lows. The challenge is to indicate every Elliot wave in a df.
Hi, happy to read your name :-)
Thanks for watching and thanks for the suggestion.
Very interesting 🧐 thank you
Thanks a lot mate
any chance you could do a video on tradingview webhooks and python?
Not planned in the near future, but noted. Thanks for your suggestion!
Great video as it's very instructive. However, I think the signal itself is complete bollocks.
But the great thing is you have shown us how to piece and parse the data together to think up and code our own signals to test. Thank you.
Thanks a lot man. Also thanks for sharing your thoughts!
Couldn't you just grab the current price 6 months ahead and compare with the entry price? Not sure why we need the cumprod/accumulate all days in between. Cheers!
He has other videos for stock price returns with explanations :)
Cheers mate! Yes, you can. In that case you would just screen for the very last entry in the subframe and divide that by the very first entry.
Is Algovibes using a website or program to run his python? If so which one
Using Jupyter Notebook here. Be invited to check out the Python Introduction playlist. I am introducing all tools I am using there.
@@Algovibes by the way, have already showed in some other video how to use python to send real time orders mainly for stocks? Something like using the interactive brokers API or alpaca? I know you have done that for crypto using binance. Thanks for the great content!
Thanks
Thank YOU! :-)
Wouldn't you combine this with a stop loss? You'd need to be gutsy to hold blindly for 6 months if you were headed for -30%.
Sure. I was just testing the strategy as described in the article. There is probably a lot of improvement potential. In general the strategist just wanted to show the good buying opportunity in those situations.
@@Algovibes Thanks, and for your content 👍
WOW 😜🤗🤗💕💕🤑🤑💷💶💴💵
😀
@@Algovibes 😳❤️❤️