Built from a decade of obsession with markets.

For over ten years I've worked as a Solutions Architect and Data Analyst. My days are built around patterns — finding signal in noise, turning complex systems into clear decisions. I love the work. But somewhere alongside it, a second obsession quietly took root: finance, global markets, and the mechanics behind why capital flows where it does.

I wasn't drawn in by get-rich-quick promises. I was drawn in by the history — the patterns that repeat across decades, the macro forces that shape cycles, the way fear and greed leave legible footprints in the data. I spent years reading case studies, studying historical drawdowns, dissecting what separated investors who survived crashes from those who didn't.

Crypto, specifically, felt like the most data-rich, pattern-dense market I'd ever encountered. On-chain transparency that traditional markets don't offer. Sentiment cycles so clean you could almost set a watch by them. So I studied it the way I study everything: obsessively, with data, and with a healthy respect for what I didn't yet know.

At some point, studying from the sidelines wasn't enough. I wanted to know if the frameworks I'd built — the risk signals, the cycle indicators, the macro overlays — actually held up when real money was on the line. So I started deploying my own capital using the same principles this tool now codifies, trading the indicators live, by hand, through everything the market has thrown at them since. Those were my own judgment calls on charts, not a published model — the specific numeric weights came later, and I keep the two claims separate on the methodology page.

The core idea was simple but disciplined: buy when risk is low, reduce when risk is high. Not market timing in the classic sense — more like a systematic approach to position-sizing based on where we are in the cycle. When the on-chain metrics, macro signals, and sentiment data all converged to say "this is historically a low-risk zone," deploy more. When they said "this is historically a dangerous zone," hold back.

More importantly, it survived the periods that test every investor's conviction — the drawdowns that wipe out overleveraged positions, the euphoria cycles that tempt you to FOMO in at the top, the macro shocks that cause panic selling at exactly the wrong moment. The model helped me stay rational when the market was anything but.

I know what it feels like to watch a market move and have no framework for what to do. To see headlines screaming "crypto is dead" and not know if this is the moment to buy the dip or step away entirely. To watch friends make financial decisions driven by influencers who have every incentive except the honest one.

The tools institutional investors use to navigate these markets — the macro overlays, the on-chain analytics, the systematic risk frameworks — they exist. They're just usually locked behind Bloomberg terminals and fund subscriptions most people will never access. That gap felt wrong to me.

I spent years building these tools for myself. The natural next step was to make them available to anyone who wants to approach crypto research with the same rigor professional analysts apply to traditional markets. Not to make decisions for you — but to give you the same clarity I have when I sit down to review my own positions every week. That's Alphabit: a decade of self-directed study and real-money testing, packaged into tools that are honest about what they know and what they don't.