Cohesive Stock Strategy Development

Hello. Do you need help finding some new stocks for your watchlist? Maybe we can find stocks based on their Volume or Market Cap?

I want to create a new strategy based on the following instruction/information

Simple Beta Baller Signal Strategy (IEF > IBTK, SHY > SBND, with SOXL, SOXS, SQQQ, TECL components)
Strategy Overview
This strategy dynamically allocates between bond ETFs (SHY, IEF, SBND, IBTK) and leveraged semiconductor and tech ETFs (SOXL, SOXS, TECL, SQQQ) based on relative strength signals and RSI-based oversold/overbought conditions.

The strategy relies on:

Relative Strength Comparisons

If IEF (10-year Treasury bond ETF) is stronger than IBTK, bond ETFs are favored.
If SHY (1-3 Year Treasury Bond ETF) is stronger than SBND, bond ETFs are favored.
RSI-based Entry and Exit Signals

If SPY RSI > 75, favor SHY (defensive allocation).
If SPY RSI < 30, favor high-beta semiconductor ETFs (SOXL).
Oversold Conditions for Leveraged ETFs

If SOXS (bear semiconductor ETF) is overbought, take long positions in SOXL and TECL.
If SQQQ (bear QQQ ETF) is overbought, consider long positions in SOXL and TECL.
Stop-Loss and Take-Profit Considerations

The backtest shows a high return-to-risk ratio, implying a risk-managed exit mechanism.
It is unclear if stop-loss orders or trailing stops are explicitly used, but given the large drawdowns in leveraged ETFs, it's advisable to introduce fixed SL/TP levels (suggested: 5-10% SL, 10-20% TP).
Performance Metrics (From Backtest)
Total Return: +225.4%
Sharpe Ratio: 1.84
Max Drawdown: Unknown (but likely high due to leverage)
Slippage & Fees:
Regulatory Fees: $2,370.78
Total Slippage: $14,768.90
Trading Pass Cost: $840
Observation:

The strategy is highly effective during risk-on market cycles (bullish tech cycles) but may underperform in high-volatility or sideways markets.
Fine-tuning RSI thresholds and incorporating volatility-adjusted position sizing could improve risk-adjusted returns.
Rebuilding Considerations for Aurora Bot
Unknowns / Clarifications Needed
Position Sizing:

Does the strategy allocate equal weight to all positions, or does it scale based on RSI/strength differentials?
Suggested: Adaptive position sizing based on volatility-adjusted ATR or max risk exposure per trade.
Trade Execution Timing:

Is trading executed daily, weekly, or intraday?
Suggested: A daily rebalance is inferred from the backtest description.
Entry & Exit Rules for Bonds vs. Equities:

What conditions explicitly trigger switching from bonds to equities?
Suggested: A rolling relative strength comparison between SHY vs. SBND and IEF vs. IBTK.
Stop-Loss Mechanism:

Are hard stop-losses placed, or is it purely a mean-reversion-based trade?
Suggested: Implement dynamic ATR-based stop-losses.
Handling Market Regimes:

Does the strategy completely shift between defensive and aggressive allocations, or maintain hybrid exposure?
Suggested: Allow partial allocations rather than full shifts to improve stability.

Based on the information you provided, here are a couple of strategies that align with the Simple Beta Baller Signal Strategy:

The first strategy would be to buy leveraged semiconductor and tech ETFs (SOXL, SOXS, TECL, SQQQ) when SPY’s RSI is below 30. This means we favor high-beta semiconductor ETFs when the market is oversold.

The second strategy would be to buy bond ETFs (SHY, IEF, SBND, IBTK) when SPY’s RSI is above 75. This means we favor defensive allocations when the market is overbought.

The third strategy would be to switch from bond ETFs to leveraged semiconductor and tech ETFs when IEF is weaker than IBTK and SHY is weaker than SBND.

The fourth strategy would be to take long positions in SOXL and TECL when SOXS is overbought. This means we consider long positions in SOXL and TECL when the bear semiconductor ETF is overbought.

The fifth strategy would be to take long positions in SOXL and TECL when SQQQ is overbought. This means we consider long positions in SOXL and TECL when the bear QQQ ETF is overbought.

The sixth strategy would be to sell 5% of your position value in SPY when SPY’s price moves down 2% in 3 days. This means we favor defensive allocations when the market is overbought.

The seventh strategy would be to sell 5% of your position value in SPY when SPY’s price moves up 2% in 3 days. This means we favor defensive allocations when the market is overbought.

The eighth strategy would be to dynamically adjust positions based on a rolling relative strength comparison between SHY vs. SBND and IEF vs. IBTK. This means we dynamically allocate based on the relative strength of the bond ETFs and leveraged semiconductor and tech ETFs.

The ninth strategy would be to implement dynamic ATR-based stop-losses to manage risk. This means we dynamically adjust stop-losses based on the average true range (ATR) to manage risk.

Do you agree with these strategies? Do you want to generate the JSON or do you need to make any edits?

could it not all come together into one cohesive strategy?

Based on your request, I will create a single cohesive strategy that incorporates all the elements you mentioned. This strategy will dynamically allocate between bond ETFs and leveraged semiconductor and tech ETFs based on relative strength signals and RSI-based oversold/overbought conditions. Here is the strategy in JSON format:
This strategy dynamically allocates between bond ETFs and leveraged semiconductor and tech ETFs based on the specified conditions. Let me know if you need any adjustments or further details!

My Apologies. I seem to have encountered the following error: "Error: Received the following error while creating the indicator: Error validating indicator "# of Days Since the Last Completed ": DaysSinceTransaction indicators must have a type".

This can be due to a variety of reasons including a system error or user error. Please try the following actions to resolve this error:

1. Click "Clear Action" on the top center of the chat and try again.
2. Try using a different model (such as the High Performance Assistant or the Maximum Capability Model)
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