Dec 17, 2023

Daily

. - the selection mechanisms include filters like top/bottom by a metric (for example, strongest momentum or lowest drawdown), and sort options (max drawdown, moving-average returns, standard deviation). when a group selects assets, the capital weight is typically shown as a 100/100 weight (representing full allocation within that group) and can switch to cash or to other groups depending on the rule outcome. - the assets used are a mix of broad market etfs and leveraged/inverse variants to express different directional bets and hedges (for example qld, rom for levered tech exposure; qid, qsl for inverse/short exposure; sso for another levered s&p tilt; spy and qqq as core market exposures). the framework also uses standard fixed-income proxies (tlt, iei, shy, shv, bnd, bsv) and a few commodity/dollar exposures (dbo, uup) to diversify risk. - the backtest aspect is explicit: the structure contains historical backtest blocks (such as “what more do you need? (even longer backtest)” and timestamps like may 30 2007) to probe how the rules would have behaved across different market regimes and time periods. the intention is to see which combination of signals and assets would have performed best over a long horizon. important caveats about interpretation and risk: - this is a highly engineered diy strategy with many moving parts. it relies on levered and inverse etfs, which magnify both gains and losses and can behave very differently from unlevered exposures over time due to compounding and path dependence. - backtests can overfit to the data if rules are tuned to past periods. real-world results can differ due to slippage, costs, liquidity, and execution delays. - daily rebalancing in a real portfolio could incur transaction costs, bid-ask spreads, and tax implications; these factors matter in practice. - the sheer number of rule interactions makes it hard for a single, simple narrative to capture the true behavior; in practice, you’d want to stress-test simpler, more robust versions and test out-of-sample results. in short: this is a comprehensive, rule-driven, daily tactical asset-allocation system that cycles through stocks, leveraged nasdaq exposure, hedges, bonds, and cash based on momentum and trend signals across many etfs. it’s designed to test a wide range of regime-switching ideas and pick combinations that historically looked favorable, rather than to provide a single, simple buy/sell rule for a casual investor.