KukaXoco Finance - SUB-OPTIMAL STRATEGIES

We constant research trading strategies, looking for any little-known sophisticated technique we can incorporate into our systems. We thus have to sift a lot of sub-optimal to barely-useful systems. Here are such sub-optimal trading systems you are welcome to try out. Some come with Python code to make it easier to experiment.

TRADING SYSTEMS

• Norman Fosback's 'Seasonality Timing System' - by Mark Hulbert, MarketWatch, 24 March 2025
  Basically, buy the Wilshire 5000 index (the SPY pretty much trackes it) near the end of the month, and sell at the beginning of the month - and immediately prior to holidays when the stock market is closed. The rest of the time (about 66% of the time), but Treasury Bonds. From 1987 to 2022, the strategy had a simliar return to the buying and holding the SPY/Wilshire, but with the advantage of being out of the market 66% of the time.

TRADING SYSTEMS WITH PYTHON CODE

• Optimizing a Rate-of-Change Strategy with Bayesian Methods/A> - by Brian Hulela, Medium (locked), 07 September 2025
  Even with optimization, at least for Tesla from 2023 to 2025, the Rate of Change Strategy performs about the same as Buy-and-Hold. Not unexpected, but well illustrated.
• Fund Flow Strategy - by Sunil Sandhu, Medium (locked), 25 August 2025
  The system goes long by buying TLT and goes short be selling SPY seven days before the end of the month, and the reversing at the beginning of the next month (short TLT, long SPY), exiting one week later. The theory is exploiting the flows of money of institutional investors, as they rebalance around the beginning of each month. From 2010 to mid-2015, the system had an annual return of about 1.0%.