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<100 subscribers
Emily reached for her usual cup of Americano while scrolling through the news feed.
Bitcoin, after a recent surge, has entered correction again — some participants are locking in profits ahead of regulatory decisions. The same pattern across altcoins: deep pullbacks in some places, sluggish rebounds in others.
On days like these, the market stops being a place for one big idea. It's much more comfortable to operate by a different principle: not one asset and not one signal, but hundreds of small, controlled experiments.
One such experiment just wrapped up a few minutes ago. A modest SXP position on Bitget executed flawlessly. Just one trade — but it's on such building blocks that large-scale strategies are constructed, leading to substantial profits.
Emily recalled working with Money Flow Index long ago. MFI considers both price and volume simultaneously. Values below 20 mean: sellers have been pushing the market for a while, but momentum is beginning to fade. Not a guarantee of reversal, but a reason to look closer and run a small experimental position.
In the early months of working with MFI on liquid instruments, the statistics were surprisingly solid. Now it's not so much the signal logic that has changed, but the discipline and understanding of which assets reveal this indicator's potential best. Today's SXP was exactly that kind of asset.
On the SXP chart, a prolonged local downtrend was unfolding: price was sliding down in steps, MFI was marking oversold conditions, volume was leaving the asset.
At the intersection of the oversold level according to WPR, a familiar set of conditions appeared. Instead of entering with a large single position, the entry was split into four averaging orders. The spacing between them adjusts to the rate of decline: each subsequent order slightly lower than the previous one, keeping the average entry price manageable.
According to CoinGecko reports, Bitget ranks among the exchanges with the deepest liquidity for altcoins, and this was clearly felt with SXP execution: the order grid filled smoothly, without gaps or partial fills.
After one more short impulse, the asset updated its local minimum and bounced. A technical rebound of several percent, combined with leverage and a solid average entry point, turned into a clean profit on the position. The trade closed on pre-set conditions — no chasing highs, no rolling into long-term holds.
Emily recorded it in the journal:
Asset: SXP/USDT (15m, Bitget)
Signal: MFI < 20
Entry & Averaging: WPR oversold crossing at −80, grid of 4 orders
PNL: +70.52%
The key isn't the PNL figure itself, but rather:
• Risk per trade was minimal.
• SXP is one of many assets on the working list.
• The structure relied on real liquidity.
When Bitcoin alternates between new highs and corrections, and headlines simultaneously scream both "crash imminent" and "to the moon soon," it's easy to get caught on one scenario and concentrate all your attention on it.
But a different approach looks much more interesting: dozens and hundreds of small strategies, different coins, timeframes, and entry conditions. Each trade is like a small, bright lightbulb: individually it might burn out, but together they give steady light.
Some ideas work perfectly, some work decently, some take drawdowns. By splitting risk, no single mistake becomes a death sentence for the account. Today's SXP is just one of those lightbulbs. A successful one, but far from the only one.
After closing the position, Emily's gaze catches on the note stuck to her monitor again: «CHECK THE DOOR» — the same one that appeared in the previous episode.
The lock in the far corner clicks softly once more. No market signals. No open positions requiring attention. The perfect moment to finally follow through on her own reminder.
Emily pushes aside a couple of boxes with cables and opens the door wider — and finds herself not in a dim storage room, but in a lived-in space. Something between an archive, a research office, and a home workspace: shelves with folders, several old monitors, wiring running through the walls, and in the center — a massive projector on a tripod. Opposite — a large projection screen.
Questions linger: who else conducts trading experiments here? Whose desks and monitors are these?
On one film canister, neat handwriting reads:
"The Impact of Diversification on Trading Portfolio Results"
— Very on point, Emily smiles quietly and threads the film into the projector.
A beam of light falls on the screen. Slides begin:
"A Portfolio From One Strategy and One Asset Lives Their Lifecycle"
"A Portfolio From Hundreds of Small Independent Ideas Smooths Drawdowns and Survives Market Phase Shifts"
On the next frame — two curves:
First — "Concentrated Position": smooth growth followed by a sharp drop after a series of losses.
Second — "Hundreds of Small Experiments": a jagged line, but stubbornly trending upward, surviving prolonged drawdowns along the way.
Emily looked at this graph and involuntarily compared it to her own statistics: dozens of small positions distributed across different coins and ideas. Today, one more point simply appeared there — a trade on SXP at Bitget. One of hundreds...
Who recorded all this? Who conducted these experiments? And why do the conclusions align so perfectly with her own observations?
— Interesting. I should study this archive in more detail next time, she says, stopping the film.
Emily turns off the projector and returns to the terminals. She deliberately leaves the door to the room slightly ajar — as a reminder that today's trade is not a final point, but merely a fragment of a large, interesting story...
⚠️ IMPORTANT: This material is for informational and entertainment purposes only and does not constitute financial advice. Trading involves high risk. Loss of capital is possible.
Join our Telegram:
Hampfree | Market Lab (Global)
Emily reached for her usual cup of Americano while scrolling through the news feed.
Bitcoin, after a recent surge, has entered correction again — some participants are locking in profits ahead of regulatory decisions. The same pattern across altcoins: deep pullbacks in some places, sluggish rebounds in others.
On days like these, the market stops being a place for one big idea. It's much more comfortable to operate by a different principle: not one asset and not one signal, but hundreds of small, controlled experiments.
One such experiment just wrapped up a few minutes ago. A modest SXP position on Bitget executed flawlessly. Just one trade — but it's on such building blocks that large-scale strategies are constructed, leading to substantial profits.
Emily recalled working with Money Flow Index long ago. MFI considers both price and volume simultaneously. Values below 20 mean: sellers have been pushing the market for a while, but momentum is beginning to fade. Not a guarantee of reversal, but a reason to look closer and run a small experimental position.
In the early months of working with MFI on liquid instruments, the statistics were surprisingly solid. Now it's not so much the signal logic that has changed, but the discipline and understanding of which assets reveal this indicator's potential best. Today's SXP was exactly that kind of asset.
On the SXP chart, a prolonged local downtrend was unfolding: price was sliding down in steps, MFI was marking oversold conditions, volume was leaving the asset.
At the intersection of the oversold level according to WPR, a familiar set of conditions appeared. Instead of entering with a large single position, the entry was split into four averaging orders. The spacing between them adjusts to the rate of decline: each subsequent order slightly lower than the previous one, keeping the average entry price manageable.
According to CoinGecko reports, Bitget ranks among the exchanges with the deepest liquidity for altcoins, and this was clearly felt with SXP execution: the order grid filled smoothly, without gaps or partial fills.
After one more short impulse, the asset updated its local minimum and bounced. A technical rebound of several percent, combined with leverage and a solid average entry point, turned into a clean profit on the position. The trade closed on pre-set conditions — no chasing highs, no rolling into long-term holds.
Emily recorded it in the journal:
Asset: SXP/USDT (15m, Bitget)
Signal: MFI < 20
Entry & Averaging: WPR oversold crossing at −80, grid of 4 orders
PNL: +70.52%
The key isn't the PNL figure itself, but rather:
• Risk per trade was minimal.
• SXP is one of many assets on the working list.
• The structure relied on real liquidity.
When Bitcoin alternates between new highs and corrections, and headlines simultaneously scream both "crash imminent" and "to the moon soon," it's easy to get caught on one scenario and concentrate all your attention on it.
But a different approach looks much more interesting: dozens and hundreds of small strategies, different coins, timeframes, and entry conditions. Each trade is like a small, bright lightbulb: individually it might burn out, but together they give steady light.
Some ideas work perfectly, some work decently, some take drawdowns. By splitting risk, no single mistake becomes a death sentence for the account. Today's SXP is just one of those lightbulbs. A successful one, but far from the only one.
After closing the position, Emily's gaze catches on the note stuck to her monitor again: «CHECK THE DOOR» — the same one that appeared in the previous episode.
The lock in the far corner clicks softly once more. No market signals. No open positions requiring attention. The perfect moment to finally follow through on her own reminder.
Emily pushes aside a couple of boxes with cables and opens the door wider — and finds herself not in a dim storage room, but in a lived-in space. Something between an archive, a research office, and a home workspace: shelves with folders, several old monitors, wiring running through the walls, and in the center — a massive projector on a tripod. Opposite — a large projection screen.
Questions linger: who else conducts trading experiments here? Whose desks and monitors are these?
On one film canister, neat handwriting reads:
"The Impact of Diversification on Trading Portfolio Results"
— Very on point, Emily smiles quietly and threads the film into the projector.
A beam of light falls on the screen. Slides begin:
"A Portfolio From One Strategy and One Asset Lives Their Lifecycle"
"A Portfolio From Hundreds of Small Independent Ideas Smooths Drawdowns and Survives Market Phase Shifts"
On the next frame — two curves:
First — "Concentrated Position": smooth growth followed by a sharp drop after a series of losses.
Second — "Hundreds of Small Experiments": a jagged line, but stubbornly trending upward, surviving prolonged drawdowns along the way.
Emily looked at this graph and involuntarily compared it to her own statistics: dozens of small positions distributed across different coins and ideas. Today, one more point simply appeared there — a trade on SXP at Bitget. One of hundreds...
Who recorded all this? Who conducted these experiments? And why do the conclusions align so perfectly with her own observations?
— Interesting. I should study this archive in more detail next time, she says, stopping the film.
Emily turns off the projector and returns to the terminals. She deliberately leaves the door to the room slightly ajar — as a reminder that today's trade is not a final point, but merely a fragment of a large, interesting story...
⚠️ IMPORTANT: This material is for informational and entertainment purposes only and does not constitute financial advice. Trading involves high risk. Loss of capital is possible.
Join our Telegram:
Hampfree | Market Lab (Global)
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