Xer0's Dual Engine Ladder AllocatorOverview
This indicator is designed for long-term investors using a "Dual Engine" portfolio strategy on M1 Finance — mixing a broad-market index fund with a leveraged counterpart in the same Pie. Instead of guessing when to buy the dip, this script provides a systematic, step-by-step roadmap for increasing your leveraged allocation as the market falls, and resetting it as the market recovers.
How It Works
The strategy is built on "Sticky All-Time High" logic. It tracks the highest close price and calculates the current drawdown from that peak, then responds with one of three scenarios:
Ladder Down (Risk On): For every defined drop step (e.g. every -5%), the indicator signals a RISK UP event — automatically calculating your new target allocation to the leveraged slice of your Pie. This forces systematic, disciplined buying at lower prices.
Recovery Reset (Risk Off): Once the market recovers by a set percentage from the bottom, the script signals a RESET — returning your allocation to the base level and locking in the gains from the dip-buying phase.
Bull Step: When the market pushes into new high territory, the script tracks each new leg up and keeps your reference point current.
Key Features
Sticky ATH Tracking: Automatically calculates true drawdown from the cycle peak
Customizable Ladder Steps: Define your own drop trigger percentage and leverage increase per step
Max Cap: Hard ceiling on leverage exposure to protect against catastrophic drawdowns
Bar Confirmation: All signals fire on daily close to avoid intraday false triggers
Visual Dashboard: Bottom-right table showing current mode, target leverage, drawdown, and recovery price target
Alert Conditions: Built-in RISK UP and RESET alerts compatible with PulseWire's "Once Per Bar Close" setting
Backtested Performance (Simulated — Read Carefully)
The following results are from a Python backtest covering approximately 30 years (1996–2026), using $923/week in contributions every Friday. The strategy used two M1 Pies: Pie 1 (S&P 500 index fund / 3× S&P 500 ETF, base leverage 35%) and Pie 2 (Nasdaq-100 index fund / 3× Nasdaq-100 ETF, base leverage 25%). Tax assumptions reflect California state + federal rates for a $47K–$100K income bracket. Data prior to 2010 is synthetic, modeled from underlying index returns.
Results are hypothetical and do not represent actual trading. Past performance does not guarantee future results.
Ladder Strategy | VOO Benchmark
Total Contributed $1,395,576 | $1,395,576
Final Value (after-tax) $25,286,879 | $9,025,443
Total Return 1,711.9% | 546.7%
CAGR (on contributions) 10.1% | 6.4%
Max Drawdown -91.8% | -50.5%
Taxes Paid (CA) $5,358,907 | N/A (buy & hold)
Cash After Full Liquidation $23,500,189 | $7,171,385
The ladder strategy produced approximately 227.7% more after-tax cash than buy-and-hold VOO after full liquidation. However, the strategy experienced a maximum drawdown of -91.8% — meaning at its worst point, the portfolio lost nearly all of its value on paper. This level of volatility is not suitable for most investors and requires strong conviction and a long time horizon to hold through.
How to Use
Add this indicator to a Daily (1D) chart of your chosen index. Configure the inputs to match your risk tolerance — Base Leverage %, Drop Step %, and Max Cap %. Enter your M1 Pie name in the input field so alerts reference it by name. Set alerts using "Once Per Bar Close" and adjust your Pie allocation whenever a signal fires.
Disclaimer
This script is for informational and educational purposes only. It does not constitute financial advice. Backtested results are simulated and hypothetical — they do not account for all real-world frictions and should not be interpreted as a guarantee of future performance. Trading leveraged instruments involves significant risk, including the potential loss of your entire investment, and is not suitable for all investors. Indicator
Indicator
Performance Metrics With Bracketed Rebalacing [BackQuant]Performance Metrics With Bracketed Rebalancing
The Performance Metrics With Bracketed Rebalancing script offers a robust method for assessing portfolio performance, integrating advanced portfolio metrics with different rebalancing strategies. With a focus on adaptability, the script allows traders to monitor and adjust portfolio weights, equity, and other key financial metrics dynamically. This script provides a versatile approach for evaluating different trading strategies, considering factors like risk-adjusted returns, volatility, and the impact of portfolio rebalancing.
Please take the time to read the following:
Key Features and Benefits of Portfolio Methods
Bracketed Rebalancing:
Bracketed Rebalancing is an advanced strategy designed to trigger portfolio adjustments when an asset's weight surpasses a predefined threshold. This approach minimizes overexposure to any single asset while maintaining flexibility in response to market changes. The strategy is particularly beneficial for mitigating risks that arise from significant asset weight fluctuations. The following image illustrates how this method reacts when asset weights cross the threshold:
Daily Rebalancing:
Unlike the bracketed method, Daily Rebalancing adjusts portfolio weights every trading day, ensuring consistent asset allocation. This method aims for a more even distribution of portfolio weights, making it a suitable option for traders who prefer less sensitivity to individual asset volatility. Here's an example of Daily Rebalancing in action:
No Rebalancing:
For traders who prefer a passive approach, the "No Rebalancing" option allows the portfolio to remain static, without any adjustments to asset weights. This method may appeal to long-term investors or those who believe in the inherent stability of their selected assets. Here’s how the portfolio looks when no rebalancing is applied:
Portfolio Weights Visualization:
One of the standout features of this script is the visual representation of portfolio weights. With adjustable settings, users can track the current allocation of assets in real-time, making it easier to analyze shifts and trends. The following image shows the real-time weight distribution across three assets:
Rolling Drawdown Plot:
Managing drawdown risk is a critical aspect of portfolio management. The Rolling Drawdown Plot visually tracks the drawdown over time, helping traders monitor the risk exposure and performance relative to the peak equity levels. This feature is essential for assessing the portfolio's resilience during market downturns:
Daily Portfolio Returns:
Tracking daily returns is crucial for evaluating the short-term performance of the portfolio. The script allows users to plot daily portfolio returns to gain insights into daily profit or loss, helping traders stay updated on their portfolio’s progress:
Performance Metrics
Net Profit (%):
This metric represents the total return on investment as a percentage of the initial capital. A positive net profit indicates that the portfolio has gained value over the evaluation period, while a negative value suggests a loss. It's a fundamental indicator of overall portfolio performance.
Maximum Drawdown (Max DD):
Maximum Drawdown measures the largest peak-to-trough decline in portfolio value during a specified period. It quantifies the most significant loss an investor would have experienced if they had invested at the highest point and sold at the lowest point within the timeframe. A smaller Max DD indicates better risk management and less exposure to significant losses.
Annual Mean Returns (% p/y):
This metric calculates the average annual return of the portfolio over the evaluation period. It provides insight into the portfolio's ability to generate returns on an annual basis, aiding in performance comparison with other investment opportunities.
Annual Standard Deviation of Returns (% p/y):
This measure indicates the volatility of the portfolio's returns on an annual basis. A higher standard deviation signifies greater variability in returns, implying higher risk, while a lower value suggests more stable returns.
Variance:
Variance is the square of the standard deviation and provides a measure of the dispersion of returns. It helps in understanding the degree of risk associated with the portfolio's returns.
Sortino Ratio:
The Sortino Ratio is a variation of the Sharpe Ratio that only considers downside risk, focusing on negative volatility. It is calculated as the difference between the portfolio's return and the minimum acceptable return (MAR), divided by the downside deviation. A higher Sortino Ratio indicates better risk-adjusted performance, emphasizing the importance of avoiding negative returns.
Sharpe Ratio:
The Sharpe Ratio measures the portfolio's excess return per unit of total risk, as represented by standard deviation. It is calculated by subtracting the risk-free rate from the portfolio's return and dividing by the standard deviation of the portfolio's excess return. A higher Sharpe Ratio indicates more favorable risk-adjusted returns.
Omega Ratio:
The Omega Ratio evaluates the probability of achieving returns above a certain threshold relative to the probability of experiencing returns below that threshold. It is calculated by dividing the cumulative probability of positive returns by the cumulative probability of negative returns. An Omega Ratio greater than 1 indicates a higher likelihood of achieving favorable returns.
Gain-to-Pain Ratio:
The Gain-to-Pain Ratio measures the return per unit of risk, focusing on the magnitude of gains relative to the severity of losses. It is calculated by dividing the total gains by the total losses experienced during the evaluation period. A higher ratio suggests a more favorable balance between reward and risk.
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Compound Annual Growth Rate (CAGR) (% p/y):
CAGR represents the mean annual growth rate of the portfolio over a specified period, assuming the investment has been compounding over that time. It provides a smoothed annual rate of growth, eliminating the effects of volatility and offering a clearer picture of long-term performance.
Portfolio Alpha (% p/y):
Portfolio Alpha measures the portfolio's performance relative to a benchmark index, adjusting for risk. It is calculated using the Capital Asset Pricing Model (CAPM) and represents the excess return of the portfolio over the expected return based on its beta and the benchmark's performance. A positive alpha indicates outperformance, while a negative alpha suggests underperformance.
Portfolio Beta:
Portfolio Beta assesses the portfolio's sensitivity to market movements, indicating its exposure to systematic risk. A beta greater than 1 suggests the portfolio is more volatile than the market, while a beta less than 1 indicates lower volatility. Beta is used to understand the portfolio's potential for gains or losses in relation to market fluctuations.
Skewness of Returns:
Skewness measures the asymmetry of the return distribution. A positive skew indicates a distribution with a long right tail, suggesting more frequent small losses and fewer large gains. A negative skew indicates a long left tail, implying more frequent small gains and fewer large losses. Understanding skewness helps in assessing the likelihood of extreme outcomes.
Value at Risk (VaR) 95th Percentile:
VaR at the 95th percentile estimates the maximum potential loss over a specified period, given a 95% confidence level. It provides a threshold value such that there is a 95% probability that the portfolio will not experience a loss greater than this amount.
Conditional Value at Risk (CVaR):
CVaR, also known as Expected Shortfall, measures the average loss exceeding the VaR threshold. It provides insight into the tail risk of the portfolio, indicating the expected loss in the worst-case scenarios beyond the VaR level.
These metrics collectively offer a comprehensive view of the portfolio's performance, risk exposure, and efficiency. By analyzing these indicators, investors can make informed decisions, balancing potential returns with acceptable levels of risk.
Conclusion
The Performance Metrics With Bracketed Rebalancing script provides a comprehensive framework for evaluating and optimizing portfolio performance. By integrating advanced metrics, adaptive rebalancing strategies, and visual analytics, it empowers traders to make informed decisions in managing their investment portfolios. However, it's crucial to consider the implications of rebalancing strategies, as academic research indicates that predictable rebalancing can lead to market impact costs. Therefore, adopting flexible and less predictable rebalancing approaches may enhance portfolio performance and reduce associated costs. Indicator
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