[SHARE] Simple RSI BULL/BEAR strategy
(01-31-2018, 07:53 PM)tommiehansen Wrote: This strategy changes RSI-params depending on a longer Moving Average.

The general idea is quite simple: RSI between A and B works best in trend C but works less great in trend D.
So... use that knowledge to do A when B and C when D.

This could ofc be expanded upon e.g. by adding RSI-crosses and stuff like that.

Works best with short duration candles e.g. 15 minutes.

---

Backtests


XRP-USDT, dec 2017 - jan 31 2018
https://i.imgur.com/4bcYnNm.png

XRP-USDT, 2016-10-15 - 2018-01-21
https://i.imgur.com/ZoUfeaT.png

ETH-USDT: 2016-01-01 - 2017-10-05
https://i.imgur.com/Yz0t4VN.png

NEO-USDT: 2017-12-01 - 2018-02-03
https://i.imgur.com/rqHjgyM.png

---

Instructions for use

0. Make sure you got the tulip indicators installed:
npm install tulind

1. Clone the repo:
git clone https://github.com/tommiehansen/gekko_tools.git

2. Copy JS-file RSI_BULL_BEAR.js to /gekko/strategies
3. Copy TOML-file RSI_BULL_BEAR.toml to /gekko/config/strategies

---

Latest version(s)


To get the latest versions goto (and modifications):
https://github.com/tommiehansen/gekko_to...strategies

...or just clone on your drive somewhere:
git clone https://github.com/tommiehansen/gekko_tools.git

Hi TommiH. Thanks for your strategy. After five days I noticed it works the other way around I want to with EUR/BTC on Gdax. It is genrating More EUR instead of more BTC what i prefer. Howto change the settings to work it the other way arround?
  Reply
Hello Tommie,
Can you please explain these variables, I am testing but the result (buy and sell) is not according to my expectations.
Thank you and I am sorry for the noob question :/

# SMA Trends
SMA_long = 1000
SMA_short = 50

# BULL
BULL_RSI = 10
BULL_RSI_high = 80
BULL_RSI_low = 60

# BEAR
BEAR_RSI = 15
BEAR_RSI_high = 50
BEAR_RSI_low = 20

# ADX
ADX = 3
ADX_high = 70
ADX_low = 50
  Reply
Use Google and search for all these terms together with the term technical analysis e.g:
SMA technical analysis

Good luck!

(02-14-2018, 03:27 PM)dingus Wrote: Hi Tommy,

Thank you for answering,  

The strategy is tested on data for many months and in different time spans.
The tests that I've done include several roundtrips, my issue is that the roundtrips of the "real world" don't match the ones of the backtest, asif the "real world" buy and sell actions are somewhat delayed, I'm using real tight periods and 2 min candles to check its behaviour quickly.

might this be more of an overall Gekko/API issue maybe?

Yes, more of a general Gekko thing since Gekko candled doesn't match to a 100%. There's otjers that have asked similar things so if you search for it you might get some answers. I, personally, do not know.
  Reply
Thank you for your honest answer, probably I didn't explain very well.
I do know the principles of RSI and ADX, however:
My understanding of RSI for detecting overbought and oversold is very simple, on the high 70 on he low 30, when it reaches the 70 and the 30 is sold and buy signal throw the overbought and oversell signal.
On your code, you use the bull and the bear ranges right? What do you mean for Bull RSI = 10 ?

For the ADX, my understanding is the momentum of a trend, assume volatility if >20 and no volatility if <20, can you explain those 3 variables, please?

Thank you again, and i am sorry to disturb you
  Reply
The = 10 is the lenght that should be used.
The most usual RSI is 14/70/30 (lenght, high, low).

Explain the ADX? No? But i can tell you that the default values you see is based upon something that, in backtests, often has proven to work.

Set this.debugging to true @ script and check your console to get some stats at the end of each run.

(02-14-2018, 03:50 PM)Sarremans Wrote:
(01-31-2018, 07:53 PM)tommiehansen Wrote: This strategy changes RSI-params depending on a longer Moving Average.

The general idea is quite simple: RSI between A and B works best in trend C but works less great in trend D.
So... use that knowledge to do A when B and C when D.

This could ofc be expanded upon e.g. by adding RSI-crosses and stuff like that.

Works best with short duration candles e.g. 15 minutes.

---

Backtests


XRP-USDT, dec 2017 - jan 31 2018
https://i.imgur.com/4bcYnNm.png

XRP-USDT, 2016-10-15 - 2018-01-21
https://i.imgur.com/ZoUfeaT.png

ETH-USDT: 2016-01-01 - 2017-10-05
https://i.imgur.com/Yz0t4VN.png

NEO-USDT: 2017-12-01 - 2018-02-03
https://i.imgur.com/rqHjgyM.png

---

Instructions for use

0. Make sure you got the tulip indicators installed:
npm install tulind

1. Clone the repo:
git clone https://github.com/tommiehansen/gekko_tools.git

2. Copy JS-file RSI_BULL_BEAR.js to /gekko/strategies
3. Copy TOML-file RSI_BULL_BEAR.toml to /gekko/config/strategies

---

Latest version(s)


To get the latest versions goto (and modifications):
https://github.com/tommiehansen/gekko_to...strategies

...or just clone on your drive somewhere:
git clone https://github.com/tommiehansen/gekko_tools.git

Hi TommiH. Thanks for your strategy. After five days I noticed it works the other way around I want to with EUR/BTC on Gdax. It is genrating More EUR instead of more BTC what i prefer. Howto change the settings to work it the other way arround?

What your talking about has nothing to do with the strategy. Try another part of the forum.
  Reply
ok m8, thank you and sorry again
  Reply
hi
@ tommie
thanks again for sharing
Gekko made the first live trade
--
@ askmike and many thanks to all the other friends who


rsi bull bear adx
cs    5 min
wp 10

btc-usdt

buy     9500
sell    10156
buy   10094

the price drops to 9850 as you can see in the picture
there is no trade
this strategy is the right move
The first landing of trade is very sharp
subsequent descents are too soft

do you comment
thank you so much


Attached Files
.png   rsi-3-1.png (Size: 314.99 KB / Downloads: 111)
.png   rsi4.png (Size: 96.77 KB / Downloads: 82)
.png   rsi8060.png (Size: 261.78 KB / Downloads: 74)
  Reply
I've been playing around with genetic algorithms on the adx strategy using gekkoga... the analysis is still running so these figures are just a work in progress, but thought I'd share my results so far.

The risks with GA is always that it tunes very specifically to the data that you have... I still need to test these settings on data in different time frames - they're just sooo slooow to download! If someone has the data to run this on similar timeframes as tommies stunning results in his first post I'd be really curious to see the results.

EUR:ETH
GA Epochs: 342 (~5min per epoch)
Exchange: GDAX
Data: 23/5/17 - 16/2/18 (9 months)
Market Gain: 392%
Simulated Profit: 983%

Candle Length: 17 Minutes

Parameters:
Code:
# SMA Trends
SMA_long = 500
SMA_short = 42

# BULL
BULL_RSI = 12
BULL_RSI_high = 82
BULL_RSI_low = 61

# BEAR
BEAR_RSI = 11
BEAR_RSI_high = 42
BEAR_RSI_low = 26

# ADX
ADX = 2
ADX_high = 62
ADX_low = 50

Image: https://imgur.com/zsBusoU



I've had some other promising results but they've been tuned over smaller timeframes so need more work.... I want to see what's possible on smaller, more volatile altcoins - BCD and XLM might be next on the list, but I haven't researched too much so I'd be happy to hear suggestions.

Mega thanks to AskMike and Tommie for all their work!
  Reply
@ Gryphon
Hey Thanks for share.
Im curious to see that result since i have not tryed it yet myself because other issues where to be solved first.

Beeing honest; i only testing for 3 Month period. The market has changed by that much so there is much more volatility in the last three month.
If the market would move more Sideways then i reconsider to change my Strat settings.
  Reply
(02-16-2018, 10:40 AM)Gryphon Wrote: I've been playing around with genetic algorithms on the adx strategy using gekkoga... the analysis is still running so these figures are just a work in progress, but thought I'd share my results so far.

The risks with GA is always that it tunes very specifically to the data that you have... I still need to test these settings on data in different time frames - they're just sooo slooow to download! If someone has the data to run this on similar timeframes as tommies stunning results in his first post I'd be really curious to see the results.

EUR:ETH
GA Epochs: 342 (~5min per epoch)
Exchange: GDAX
Data: 23/5/17 - 16/2/18 (9 months)
Market Gain: 392%
Simulated Profit: 983%

Candle Length: 17 Minutes

Parameters:
Code:
# SMA Trends
SMA_long = 500
SMA_short = 42

# BULL
BULL_RSI = 12
BULL_RSI_high = 82
BULL_RSI_low = 61

# BEAR
BEAR_RSI = 11
BEAR_RSI_high = 42
BEAR_RSI_low = 26

# ADX
ADX = 2
ADX_high = 62
ADX_low = 50

Image: https://imgur.com/zsBusoU



I've had some other promising results but they've been tuned over smaller timeframes so need more work.... I want to see what's possible on smaller, more volatile altcoins - BCD and XLM might be next on the list, but I haven't researched too much so I'd be happy to hear suggestions.

Mega thanks to AskMike and Tommie for all their work!

hello

can you share your gekkoga config ? have been trying but after a few rounds it crashes. Also no trades are being executed by gekko when running in gekkoga
  Reply


Forum Jump:


Users browsing this thread: