Allan: How to Invest in Bittensor Subnets, TAO Galaxy, dTAO Investing, TradFi | Ep. 100
In this episode, Allan of TAO Galaxy details the construction of systematic, rules-based investment strategies for Bittensor's subnet token market. He discusses his background in traditional finance and why that industry remains hostile to crypto, the framing of bull markets moving progressively further out the risk curve toward dTAO, and why momentum measured against Bitcoin's 50-day moving average governs his crypto exposure. Allan also details the mechanics of institutional quant strategies and why the difficulty lives in the risk model rather than the signal, the explicit 2.5% position and 3% liquidity-pool constraints TAO Galaxy operates under, his morning's correlation research showing that market cap is the dominant driver of how subnets move together, the absence of any common market factor in dTAO, and the structure of the Momentum and Carry indexes delivered through non-custodial delegation proxies. *In this episode, you'll learn* - Allan's arc from traditional finance skeptic to full-time Bittensor operator, including the 2020 lockdown Bitcoin epiphany and the mining experiments that preceded TAO Galaxy - Why TradFi's hostility to crypto was partly justified, and his own estimate that "more than ninety percent of crypto projects are bullshit" - The risk-curve model of bull markets, why capital rotates from mega-cap equities outward, and why dTAO sits at the very end of that tail - How momentum works as an allocation rule rather than a market-timing call, using Bitcoin's 50-day moving average as the bull/bear switch - Why strategies at large institutional firms are "deceivingly simple" on the signal side, and how position sizing, diversification and correlation modelling are where the real work happens - The explicit risk constraints behind TAO Galaxy's portfolios, including the 2.5% cap per subnet position and the 3% cap on any subnet's liquidity pool - Why volatility is far more predictable than returns, and how volatility clustering and long-term memory
Read the article at Ventura Labs (YouTube) ↗
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