We backtest @scot1andT's slingshot strategy that helped him generate multiple triple-digit annual returns.
Learn how to #backtest using #python and #pandas. We cover importing the applicable python libraries, web scrap the Nasdaq current constituents, resample minute bars into hourly and daily bars while correcting timezone issues, and then analyze the results by creating a DataFrame and determining the strategy edge.
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00:00 Introduction
00:52 Update Python Path
01:32 Slingshot Setup Overview
02:47 Get Imports
03:17 Set Backtest Timeframe
03:47 Create Universe
04:07 Web Scrape QQQ from Invesco
06:10 Get Bar Data
07:42 Analyze Timeseries Timezone
09:10 Add Timezone
10:47 Create Indicators
12:27 Resample Timeframes
13:27 Create Hourly Bars Using pd.Grouper
16:49 Create Daily Bars
20:42 Merge Pandas Timeseries Data
21:12 Align Start and End Times
23:42 Merge Hourly & Daily Timeframes
24:12 Fill Missing Data
25:19 Create Slingshot Signal
27:42 Verify Entry Signal
29:00 Analyze Results
30:02 Loop Through Risk-Reward
31:10 Loop Through Tickers
32:02 Loop Through Bars
37:52 Create Results Dataframe
39:30 Create Summary Statistics
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