Overview: This is a long-only AI trading robot designed for a defined ladder of U.S.-listed energy-sector equities: INVX, LPG, XPRO, WKC, GEL, NEXT, and GLP. The strategy operates on the daily timeframe and searches for Rickshawman-style candlestick structures that represent a temporary pause after an established price move—a session with a relatively small real body and meaningful price extension on both sides. Rather than forecasting news, earnings, or fundamental events, the robot treats this price structure as a potential setup and waits for subsequent market behavior to validate or invalidate the trade. Positions are entered only on the long side and managed through predefined continuation and protection rules. The ticker universe follows an Energy Cap Ladder, progressing from larger to progressively smaller capitalization and liquidity profiles; as the ladder moves toward smaller-cap names, expected volatility, execution risk, spread sensitivity, and liquidity risk increase materially.
The 60-Minute ML layer acts as a secondary analytical layer beneath the daily Rickshawman setup. While the daily chart defines the strategic trading opportunity, 60-minute market data can be used to evaluate shorter-horizon price behavior, volatility, momentum, volume, and intraday structure surrounding the setup. The ML component is intended to rank or filter the quality of potential entries rather than replace the core pattern logic. In this architecture, the daily Rickshawman signal establishes the candidate trade, while the 60-minute model provides additional context for execution timing and risk assessment. The system therefore combines an interpretable daily pattern with a higher-frequency quantitative layer while preserving deterministic entry, exit, and protection rules.
An inverse ETF (Exchange-Traded Fund) is designed to provide investment results that correspond to the inverse of the daily performance of a specified index or benchmark. Leveraged inverse ETFs seek to amplify this inverse exposure by a predetermined multiple, providing a tactical instrument for strategies designed to respond to declining market conditions.
The trading robot incorporates ERY (Direxion Daily Energy Bear 2X ETF) as its inverse market exposure component. ERY seeks to deliver 200% of the inverse (-2X) of the daily performance of the Energy Select Sector Index, providing leveraged inverse exposure to the U.S. energy sector.
The inclusion of ERY enables the trading strategy to take tactical positions during periods of weakness or negative momentum in energy-sector equities. This expands the robot’s ability to operate across different market environments and provides an additional instrument for managing directional market exposure within the overall strategy.
As a leveraged inverse ETF, ERY resets its exposure on a daily basis. Due to the effects of daily rebalancing, leverage, market volatility, and compounding, its performance over periods longer than one trading day can differ materially from two times the inverse of the cumulative performance of the underlying index. These effects may become more pronounced during periods of elevated volatility.
Accordingly, ERY is utilized as a tactical trading instrument rather than a long-term inverse position, with its exposure managed within the robot’s broader trading and risk-management framework.
The Rickshawman AI Trading Robot systematically identifies periods in which price appears to pause after a directional move. In practical terms, it looks for a daily candle with a small body and shadows extending in both directions—a market state in which neither buyers nor sellers achieved decisive control during the session. The robot does not assume that this candle guarantees either a reversal or continuation. Instead, it treats the pattern as a conditional opportunity and waits for subsequent price action to satisfy its entry criteria. Once a long position is initiated, the robot manages the trade according to predefined protection and continuation logic. Compared with slower or more selective strategies, Rickshawman is designed to feel more active: qualifying setups and resulting trade-management events may occur more frequently, although actual activity remains dependent on market conditions.
Rickshawman is a pattern-driven, long-only systematic strategy rather than a conventional Buy/Sell scoring model. Its primary technical foundation is daily OHLC price structure, with the Rickshawman candle acting as the recognizable setup around which the trading logic is organized. The strategy separates setup detection, confirmation, execution, protection, and exit management, reducing dependence on discretionary interpretation. It does not attempt to trade earnings surprises, headlines, analyst ratings, or macroeconomic news directly. The 60-minute ML layer can complement the daily signal by measuring shorter-term market conditions, but the system remains anchored to explicit technical and risk-management rules. The eligible universe is deliberately narrow—INVX, LPG, XPRO, WKC, GEL, NEXT, and GLP—allowing the same strategic framework to be applied across different capitalization, volatility, and liquidity regimes within the energy universe.
Quantitative thresholds should be defined separately for signal qualification, execution, position sizing, and portfolio risk rather than assuming that one threshold is appropriate across the entire Energy Cap Ladder. Core controls may include minimum liquidity requirements, maximum acceptable bid-ask spread, volatility-adjusted position sizing, maximum capital allocation per ticker, stop or protection distances derived from price volatility, maximum portfolio exposure, and predefined exit conditions. Thresholds should become progressively more conservative for smaller and less liquid securities because identical nominal position sizes can produce substantially different market-impact and drawdown characteristics. Any numerical limits used in production should therefore be calibrated and validated from historical and out-of-sample data rather than presented as universal constants.
The strategic premise is that a temporary equilibrium after a directional move can create an observable point from which subsequent continuation can be traded systematically. Rickshawman does not need to predict the market's narrative; it needs the price setup, confirmation, and risk/reward characteristics to satisfy its rules. Risk attribution is especially important because the Energy Cap Ladder intentionally spans securities with different capitalization and liquidity characteristics. Performance can therefore be decomposed into pattern-selection risk, market-direction risk, energy-sector concentration, individual-security risk, volatility exposure, liquidity and spread costs, execution slippage, model/filter risk, and position-sizing effects. Smaller-cap variants can produce stronger percentage movements but simultaneously introduce materially greater volatility, liquidity, gap, and execution risks. Rickshawman should consequently be viewed as a rules-based framework for capturing qualified daily price pauses—not as a guarantee that a pause will lead to continuation or that any individual trade will be profitable.
Maximum Open Positions: Medium, allowing for diversified exposure while managing concentration risk.
Robot Volatility: Low, attributed to the strategic entry after minor pullbacks and careful position management.
Universe Diversification Score: High, indicating a broad array of instruments to hedge against sector-specific downturns and enhance profit opportunities.
Optimal Market Condition High: If the current market volatility is Medium, then you should use the Best Robots in a Medium Volatility Market (VIX is Medium - this indicator is coming soon).
Disclaimer: Disclaimers and Limitations
Simulated Performance: All simulated performance results are derived solely from real-time calculations using historical data. Algorithms receive minute-by-minute historical prices and other data from Morningstar and generate trades in real time based on these historical inputs, effectively eliminating any hindsight bias.
Actual Performance: All actual performance results are derived solely from real-time calculations using current data. Algorithms receive minute-by-minute current prices and other data from Morningstar and generate trades in real time based on these current inputs, effectively eliminating any hindsight bias.
Gross Performance: Gross performance results do not deduct any fees or expenses. These results reflect the total returns generated by the AI Robots without considering the costs associated with accessing the service.
Net Performance (current performance chart): Net performance results deduct fees to provide a more accurate representation of returns experienced by the user. These deductions can include: Model Fee Deduction: Net performance results may deduct a model fee equivalent to the highest subscription fee charged to the intended audience. Actual Subscription Fees: Net performance results may also deduct the actual subscription fees paid by the user for access to AI Robot
This Robot is recommended to be used when the markets are growing in general. The core algorithm makes only long The core algorithm makes only long