We take a claim that circulates about the markets, measure it with public data and publish the result. All of them are free, with no sign-up and no recommendation of any kind.
How they are made. The data is public and the calculations are written out so anyone can repeat them. We always say how many observations were measured, over what period, and what would have to happen for the conclusion to fall.
And we publish what goes wrong for us. Every report has a section with our own mistakes. It is not decorative humility: it is the one thing a reader cannot fake having.
If you find a mistake, write to us. We correct it right there, in public. hola@sophronepsis.com
If your account has a limit on open positions, there are days when more marks arrive than fit, and what decides which ones get in is usually chance. We measured how much that chance weighs: it weighs more than almost everything we were comparing.
It is the first number people show and the most reassuring one. It is also the easiest to raise without improving anything. We tightened the filter of our own system to check it, and the opposite of what we expected happened: the result went down and so did the hit rate.
The question comes up again and again and almost nobody answers it. It matters less how many years you have than how many pieces you split them into: here is a case of ours where splitting them in half changed which version went into the system.
«Buy when the average holder is at a loss.» We tested it with two different comparisons, both reasonable. One says it does not work; the other, that it gets 18 out of 18 right. Both are true — and what decides it is not in the market, it is in what you compare it against.
There is a way to measure how much bitcoin holders are suffering. In the three completed winters it rises cycle after cycle —0.564 → 0.690 → 0.754— and at this cycle's low it stayed at 1.103. If that continues, the threshold everyone is waiting for may not come back.
It looks like an objective figure. We calculated it in two defensible ways, and one says the market is 20 % above that price; the other, 27 % below. Same day, same data, correct arithmetic in both. The difference lies in who you include in the average.
When the price falls below what it costs to mine, some miners switch off their machines, and the network's computing power drops. There is an indicator that claims to read that — the hash ribbon — and we measured it. The first result was our own mistake: counting wrongly we got 35 signals in thirteen years and were about to publish that it does not work. Counted correctly, there are 19.
The halving gets credited with the whole cycle. What it does is one specific, verifiable thing —it cuts new issuance in half— and what it does not do is mark a date on the calendar, because it does not happen on a day: it happens at a block height.
The time distances between the milestones of the three complete cycles. Bottoms are given with three different definitions —the lowest day, the lowest week and the lowest month— because with only one the precision is misleading. It is an estimate of when, not of how much.
We measured 129 ways of starting to buy bitcoin little by little. Just by changing the day you take the snapshot, the best entry point becomes the worst. In nine out of ten windows the bottom zone comes out among the best; in one, the worst of all — and that one was the one we had chosen.
The chain does not know what day it is. We reconstructed the block height day by day and something came out that we did not expect: between bottoms there is a difference of thousands of blocks, but of only six calendar days. It is a rejected strategy candidate, and it is published anyway.
A claim repeated in hundreds of videos about leveraged ETFs that does not describe what the product does. In July chip stocks fell 21.20 % and the «3X» product fell 56.99 %, not the 45 % that gets passed around. And what really hurts it is not the crashes: it is the boring months.
Where a bitcoin bear market ends, measured along five different paths over the three cycles that exist. With the control group, which is almost never published: what buying on a random date returns. And with the conditions, written in advance, that would break each path.
How much to risk on a trade is not a hunch: it is a calculation. The tool does it and, if you want, sends the order for you.
Everything on this page is educational material. It is not financial advice or a recommendation to buy or sell anything.