Economic thesis, loosely defined: Thanks to Kory and Cezar Alvarez, I present a strategy that one could trade, but looking at the tear sheet and the equity curve I suspect that this strategy is its current form and the current market does not perform. For equity curve jockeys: I'm not trading this strategy, needs more time and trading guards and I would wait to see whether the strategy is going back to older levels of volatility as the DD in the last 2 years is double from the years before.
Hi Peter, Just have to say your previous volatillity algo was so precious for me! I have implemented it in IB and it was great!
Why advanced trade bot 2x rsi buy back cheap tactics think this isn't compatible for LIVE? I thought I release it to the community and see how others can improve it. The things that I see in the tear sheet looks like the behavior as changed from to There is a big difference in returns and beta and that worries me a bit.
Advanced trade bot 2x rsi buy back cheap tactics a few more guard rails and cash usage it could be traded, but be careful Peter, i borrowed your codes and put this together. It is looking good. So wanted to give it a run in IB. I so new to Python and Q so hope you dont mind. The equity curve of the modified algo looks really nice.
What are the main logic differences between the modified and original algos? Peter, from my observation as the same as the note you put on top of MVP algo. Im not sure how can i do it in Python since im so new as this. Also here is the version that aggressive tilt and using your Vol ago to control the portion of xiv and increase or decrease portion of spy and edv.
I've shared my volatility strategies with Cesar and we're both working on improving them. Here's our Meetup group if anyone in the Seattle area is interested in joining: Please message or email me in private if you would like to collaborate with me on coding volatility strategies. I would love to have them ported over to Python for Quantopian. I have everything coded in EasyLanguage so it would be pretty easy for a programmer to port everything over.
Unfortunately I'm not a programmer. Only issue advanced trade bot 2x rsi buy back cheap tactics that the last ago does have some leverage. Any way to ensure there is no negative cash - for Robinhood trading? For anyone considering live trading NHAT NGUYEN's algo, keep in mind that it's highly dependent on day of the week, this is a form of overfitting and there's no guarantee that it's performance in the future will be as good.
Luke, you are right "there's no guarantee that it's performance in the future will be as good". These are best parameters which deliver the highest return.
For live trading, we may need some nice Python advanced trade bot 2x rsi buy back cheap tactics in the forum to double iron some bugs in order management, keep track trades, and money management part. Or lower the allocation and watch it like a hawk for couple of months. Just a word of caution: That might potentially be dangerous in the future. Kory, that's a great idea. This wouldn't work well for live trading until after some time had passed.
Here is advanced trade bot 2x rsi buy back cheap tactics correction of the depretiation warning line I would like to say it seems no body has done a back testing which covers the time period where there was big crash bcz. If you do a back testing covers this period, you will find the return is quite different.
Some of the ETFs used in this algo have no data before This could be the reason why no back testing did which covers the year of Given "Some of the ETFs used in this algo have no data before ", therefore, "no body was able to do a back testing which covers the time period ". This is already True statement. What are you saying? Maybe - put another way - the concern is that the specifics of this strategy dictate that the backtesting and subsequent walk-forward analysis have only been done in the relatively known and predictable post market conditions.
That certainly is a concern I would have prior to launching a long-term based strategy - how would it have performed during a major market turndown when correlations change dramatically between the ETFs it uses? My first objective was reduce the volatility of over all portfollio when i combined these 2 strategies and it accomplished. Second objective, was optimized and get the backtest results so i can have a advanced trade bot 2x rsi buy back cheap tactics reference point of results so i can work with when moving forwad that was the stage that i publish the backtest.
Third objective, given objective 1 and 2 met and return slightly above benchmark, can i add another strategy to reduce further beta, increase alpha and reduce volatility This is the current state that im in Fourth objective, if 1,2,3 met, moving to asset allocation models selection and various optimization techniques parameters, time reference point etc for over all portfolio and all the strategies combined.
My questions to you is? Why do you want to put your money at risk when you are clearly not putting enough time to understand how things work. You wrote a lot here. Why not simply back test your algo in bear phase? For example include the year and ? In there was a big crash bcz. After that, exactly to say since the market goes up continuously. It's a bull market.
Why not back test your algo in a bear market? I'm a very very short term trader, so if it works this year, it's good enough for me to use. I don't hold any positions overnight. I'm aware that because of this my opinion in the matter is moot to most if not all of you guys in the forum because advanced trade bot 2x rsi buy back cheap tactics trade much longer time frames.
But since I was hanging around I just threw my hat into the ring. Also, asking why no one backtests this prior to almost seems like a rhetorical question, as some of the components didn't exist before then. This too, is moot. This is Peter's thread so i dont want to post something which doesnt add any value here. And this is will be my last post here.
First, These are not mine algos, i saw some great things in Grant and Peter' algo so i try to build a something out of it to see how much volatility it can reduce. I think your logic does have serious problems. Lets me point it out for you. You said " Some of the ETFs used in this algo have no data before ". So your declaring statemnt is TRUE. You see Mr Chang, your opening statement and your conclusion can go both ways backward and forward. Is advanced trade bot 2x rsi buy back cheap tactics right Mr Cheng?
Can you see it. Could someone explain to me the basis of the algo, i am new to quant and would like to understand what the parameters are and the rationale behind this algo. Here is my understanding of this strategy: Not sure why this number used?
But does nothing if the WVF under Because the algo over-allocates to the treasuries, and the reliance on treasuries as safe haven asset that might be wrong during the tightening economic cycle.
It should be a safer bet in case of the bonds bear market. Maxim, that is a good idea. I can wait to play with this idea.
It is quite interesting and it looks promising by showing low draw-down with high Sharp. My idea is having a diversify portfolio of strategies between 2 and 4 with continuous allocation between advanced trade bot 2x rsi buy back cheap tactics. Safer and better returns. Have fun and good luck.
After I run the back testing I found in "Transaction Details" that it happens very often that an ETF is bought but several hours later at the same day it is sold again. Is this what you want?
Thank you guys, I am really glad that I could make a little contribution to this thread. Thank you for your suggestion on how to combine the strategies and use the MVP algo to drive the allocations between them. I will be investigating it… Thomas, you are right that the algo can open and close the positions in the same ETFs during the day.
The possible improvements are: Should work for long only, it doesn't short anything but using Short ETF instead. Your contribution to Peter's original code or to Maxim's?
I may apologize for my poor english. The issue still remains that there is a fixed value for the WVF trigger - using the best historically from forward. Seems like overfitting as this number can change walking forward.
I could change, but remember volatility is not a stock price or so, if the volatility structure changes permanently, othe very base assumptions in the amrket must have changed as well.
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