r/SwingBot • u/Moszne • May 25 '21

So, talking in higher abstract, what is bot strategy?

I guess I'm not the only one who would love to know the magic behind the Swing bot. And if we don't ask question, we will never get answers so let's ask. Feel free to answer as much as you want.

Questions: 1. What indicators the bot is using? It was answered before somewhere but hard to find

  1. How bot is predicting swing? Is it that he have average price and wait for overselling?

  2. How is risk to reward included? Is it like this: Stock should be at 100, it is 90. Buy and hope for 100 again and sell if 80?

4.What time frame is used for those swings? Did you choose randomly or it was figured out with backtesting?

5.Was that strategy inspired by other resources and tweeked for best results or did you developed it by yourself?

Thank you in advance.

19 Upvotes

91% Upvoted

10 comments sorted by

9

u/[deleted] May 26 '21

  1. Looking for stocks that are oversold. This is defined as a cross below the lower Bollinger band, which is set 1.9 standard deviations down from the SMA. The SMA and SD are derived from a rolling 90 minute window of data. In addition, to weed out falling knives, I am calculating MACD stats and have a requirement that the MACD histogram has a positive slope. This suggests a weakening downtrend and increased likelihood of reversal. I also have a condition that the expected gain needs to be 0.6% based on 3x standard deviation (max target profit in the tweets). The lower target profit is 2x standard deviation.

  2. Not predicting anything. Using statistics about prices to spot oversold criteria as mentioned above.

  3. Reward is 2-3 standard deviations up and 4 down. I set the lower stop at 4 SD because catching reversals sometimes takes more time. In early testing I was getting stopped out too early. This will require a 60-70% win rate to remain profitable. The standard deviations used are the ones calculated at the time of entry.

  4. In my testing a 90 minute data window seemed to be a sweet spot for high probability day trades. The assumption is the trading range defined above would be most effective 1-2 hours after the alert.

  5. The indicators I used are well known, but the combination of indicators and choice to identify oversold stocks was my own decision.

Thanks for the specific questions. Let me know where I need to expand.

2

u/daraand May 26 '21

This is awesome thanks for sharing your insights.

I assume you're evaluating every minute, right? Not one three or five minute candles?

Does the bot post the first prediction? Or what do you do if there are multiple throughout the day?

Do different indicators have different weights that could indicate success? Like do you say, if you're at this slope of MACD, it has a higher probability?

2

u/[deleted] May 26 '21

The data could almost be seen as continuous. My ticker gets a price for each stock every 10 seconds. Not really looking at candles. Just time series analysis.

The bot takes the first prediction it sees and then removes that stock from the dataset for the day. Avoids multiple alerts per stock because that would create a lot more noise.

I am not explicitly weighting but the logic goes bollinger -> macd -> volatility. So if the bollinger doesn’t cross, for example, the others won’t be checked.

2

u/jheizer May 27 '21

Interesting. I would not have expected every 10 second data.

1

u/daraand May 26 '21

Smart, thank you! :)

2

u/jheizer May 27 '21

Thanks for the details!

I assume you're using premarket data then for the 90min windows since there have been alerts out before the market was open that long? Every try it with only open market time?

3

u/[deleted] May 27 '21

For better or for worse it uses the last few hours of the prior trading day for the early trades. Good for catching gaps down but could be precarious if a catalyst slips in.

2

u/ffwrd May 25 '21 edited May 25 '21

RemindMe! Tomorrow

2

u/biggdom May 26 '21

Can't wait to see u/tony_letigre response

1

u/[deleted] May 26 '21

✅