A daily, rule-based tech-stock picker that ranks a dozen big-name techs using RSI momentum, moving-average and volatility signals, then buys a single stock (often with a specific weight) and uses volatility/ bear ETFs as hedges to manage risk. It’s a highly layered, multi-signal approach aimed at catching the day’s strongest tech momentum while hedging against spikes in volatility.

- The pool of tradable assets is a defined set of big tech names (examples include AAPL, MSFT, NVDA, AMZN, GOOG, META, TSLA, TSM, AVGO, ORCL, SAP, NFLX) and sometimes market proxies for comparison. - For each ticker, the system computes signals using momentum, trend, and volatility concepts drawn from RSI (momentum), moving-average comparisons, and standard deviation of returns. The RSI lookbacks mentioned include windows around 10, 14, 28, up to 60 days, and thresholds like 79 (overbought) and 35 (oversold) are used to judge whether to tilt long or to tilt short. Moving-average-return signals are evaluated over short (e.g., 10 days) and longer windows (e.g., 20–40–60 days) to gauge recent performance versus longer-term trend. Volatility signals (standard deviation of returns) help rank how stable or erratic each stock has been. - The algorithm ranks candidates using top/bottom filters across different signal types (relative-strength-index, moving-average-return, standard-deviation-return) and windows, then selects a single asset per day (select-n = 1 in many branches). The final pick is often accompanied by a weight (e.g., weight 60/100 or 40/100) that defines how much of the portfolio is placed in the chosen asset; sometimes a 100% weight is used, other times an internal split exists to allow hedging or partial exposure. - In parallel, the strategy includes hedging or speculative bets using leverage/volatility ETFs (UVXY for volatility, SQQQ for bear-on-QQQ, SPXS for bear-on-SPY, UUP for dollar exposures, plus treasury-based funds like BIL and TLT) to be used either as backup positions or as part of the overall risk management logic. The hedges are not automatic “longs” on equities; rather, they are used where reflected signals suggest risk-off or to capture volatility spikes. - The structure features many layers called groups (e.g., MAR x 30D RSI, PP TECH Nav, RSI x 14D MAR, Entropy Hunter, etc.). Each group applies a slightly different signal mix or asset exclusion (e.g., “No MSFT” or “No AAPL”) and then flows into an overall decision. This multiplicity implies a risk-management approach where the system tests many permutations and then picks the final asset under a larger set of rules. - Rebalancing is daily, meaning the system reviews signals, recalculates rankings, and adjusts the single daily position and any hedges. This is not a long-hold strategy; it’s a fast, rule-based, signal-driven picker that intends to ride the day’s strongest momentum in the tech space with hedges to manage risk. - The design is quite sophisticated and data-driven, but it is also highly complex and may be sensitive to parameter choices (windows, thresholds, and weighting). It’s effectively a large, automated signal-marmalade that translates momentums and volatilities into a daily single-asset conviction plus hedging. Note: understanding the exact behavior on any given day requires running the model or reading a live log; the high-level intent, however, is to buy the top momentum tech idea while employing volatility/risk hedges, and to do so every trading day.

Low market beta (~0.06) plus a daily, rule-based tech momentum strategy with hedges. Out-of-sample Sharpe ~0.60 and Calmar ~0.65 offer positive risk-adjusted upside and diversification versus SPY, with volatility protection during spikes.