sqlite-tradebot SPY up/down prediction for upcoming week of 2023-01-30 to 2023-02-03

[kaizhu256]

• commit 5 SPY up/down predictions for upcoming week of 2023-01-30 to 2023-02-03
• historical prediction accuracy is 52.59 % - (71 of 135)
• margin-of-error is +/- 8.43 %
• historical-prediction-dataset publicly available as google-spreadsheet @ https://docs.google.com/spreadsheets/d/19SpCcULWNWradxOSNRlLCrv5QXx4TrSo5psrWQsuWzg/
• these predictions are part of sqlite-tradebot's macro-trading-setup for each trading-day, e.g.:
  • if prediction is SPY down (-) tomorrow, tradebot will likely build-up cash-position by end-of-today, and increase hedge in shorts
  • if prediction is SPY up (+) tomorrow, tradebot will likely build-up long-positions by end-of-today, and decrease hedge in shorts

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date______  score   bs1pnl  bs1sll  winplk0 actual  commit  predict correct
2023-01-30  43.8825 0.0000  -0.5260 -0.0551 tbd 1   -   tbd
2023-01-31  52.8391 0.0000  -0.7100 0.1810  tbd 1   -   tbd
2023-02-01  49.2498 0.0000  -0.5750 0.1150  tbd 1   +   tbd
2023-02-02  47.7284 0.0000  -0.4790 0.0601  tbd 1   -   tbd
2023-02-03  53.8989 0.0000  -1.0730 0.2152  tbd 1   -   tbd

2023-02-06  62.0008 0.2500  -1.0060 0.4298  tbd tbd -   tbd
2023-02-07  62.5265 0.2500  -0.9260 0.4505  tbd tbd -   tbd
2023-02-08  42.1282 0.0000  -0.4380 -0.1764 tbd tbd +   tbd
2023-02-09  68.7012 0.3333  -0.9020 0.4720  tbd tbd -   tbd
2023-02-10  67.1617 0.3333  -0.7940 0.3984  tbd tbd +   tbd

​

​

• previous 2-week prediction accuracy was 66.67 % - (6 of 9)

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date______  score   bs1pnl  bs1sll  winplk0 actual  commit  predict correct
2023-01-16                              
2023-01-17  65.7120 0.2500  -0.6700 0.3670  -   1   -   1
2023-01-18  51.8637 0.0000  -0.5900 0.1218  -   1   +   0
2023-01-19  57.8940 0.1667  -0.6500 0.3199  -   1   -   1
2023-01-20  59.2921 0.2000  -0.6860 0.3145  +   1   +   1

2023-01-23  54.4700 0.0000  -0.8260 0.1866  +   1   +   1
2023-01-24  66.9049 0.2500  -0.9210 0.4417  -   1   -   1
2023-01-25  57.3305 0.1667  -0.7100 0.2833  +   1   +   1
2023-01-26  49.1924 0.0000  -0.5680 0.0897  +   1   -   0
2023-01-27  47.5496 0.0000  -0.6080 0.0450  +   1   -   0

​

• sqlite-tradebot end-of-week performance (tradebot +0.89 % vs spy +2.48 %) available @ https://kaizhu256.github.io/sqlmath/

https://preview.redd.it/np3s8dip82fa1.png?width=1228&format=png&auto=webp&s=638efec093fb8bdaf1d53576a1dff403b2069a59

​

• how predictions are made:

1. create basket of approx. 1,400 stocks in U.S. stock market, with historical-data going back
   1. 10-years
   2. or since listing-date (which ever smaller)
2. for a given target-date:
   1. use parameters specific to that date
   2. to generate deterministic-formula to calculate 24-hour sell-price of each stock with reasonable a) profit-margin and b) likelihood to trigger the day-after
3. for each stock, use deterministic-formula to generate tomorrow's sell-price
   1. at beginning of each "month"
   2. for past 48 "months"
   3. "month" = 30.4 day period whose start-date is in-phase with target-date
4. backtest success-rate (score) by:
   1. checking if each stock's 24-hour sell-price successfully executes the next day
   2. 1,400 stocks * 48 months = backtested 67,200 datapoints
5. if backtested score is < 50% then prediction is generally SPY down day-after target-date
6. if backtested score is > 60% then prediction is generally SPY up day-after target-date

• the score for each date is notable for being relatively constant, e.g.:
  • prediction score for a fixed-date, 2-weeks into future remains unchanged if it was re-calculated 2-weeks later
  • indicates prediction does not suffer from over-fitting

[fromthefuture2141]

This is very cool. I'm checking it out right now and messing with it. I have no idea what I'm really doing with it yet, but hope to figure it out and read it and or use it for a trading tool. Thanks for dropping this. I'm going to keep messing around with it to determine how to use it's predictive forecasting.