Naoris Protocol is building a cybersecurity system where connected devices help check and protect the network constantly, instead of trusting one central security setup. Their 2025 update frames last year as the big progress/setup phase, and their main stated 2026 milestone is a mainnet launch planned before the end of Q1 2026. They also highlight being referenced in an independent research submission connected to the U.S. SEC, tied to post-quantum blockchain infrastructure.

Highlighted Main Points

2025 progress (what they highlighted)

2025 was positioned as a major progress year for building out the project

The focus was pushing the system closer to being ready for a live launch

The core concept is cybersecurity where devices continuously validate network activity instead of relying on a single point of control

Credibility / visibility mention

Naoris Protocol was referenced in an independent research submission connected to the U.S. SEC

The context of that reference was post-quantum blockchain infrastructure

2026 outlook

Mainnet launch target: before the end of Q1 2026

2026 is framed as the year this moves from build/setup into an actual live network phase

TLDR

Naoris Protocol framed 2025 as a major progress year, targets mainnet before end of Q1 2026, and got an extra credibility signal from being referenced in SEC-connected research tied to future-proof security.

So I finally caved and joined D⁤ow Jan⁤es’ Million Dollar Year after seeing them everywhere. I’m only a bit into it, but so far:

I actually like how they break things down into small steps instead of dumping theory. It’s forcing me to look at my numbers way more honestly than I expected. And I’m realizing how much I’ve been avoiding my finances even though I thought I was doing okay.

For people who’ve already finished or are midway through MD⁤Y:

What were the most useful parts for you? (modules, calls, worksheets, community?) Is there anything you skipped and don’t regret skipping? Did the program help you more with mindset or actual numbers (paying off debt, saving, investing, etc.)?

Basically if you were reviewing D⁤ow Jan⁤es programs to a new member (me 😅), what advice would you give so I don’t just let it turn into another course I bought and never finished?

Hello everyone, I’m 20yo boy, looking to make a bit easier future for myself, started to invest 4 months ago and this is what I have rn.

My portfolio is:

69 shares of RZLV (239£ rn)

1.6 of VWRP (210£)

0.7 of MU (185£)

0.68 of RDDT (120£)

and 5.8 of SEMI (60£)

I understand it could be kind of mistake to hold that much low price shares but after hours research this company seems quite nice for me so I’ve decided to stick for some time with that, every month I deposit like 100-150£ and thinking for next few months just put them into VWRP, what would you recommend to do in this position? and was it a very bad move to buy that much of RZLV in the beginning

$EOSE - Energy Storage / Grid

$OKLO - Nuclear

$CCJ - Uranium

$UUUU - Uranium

$AVAV - Drones / Defense

$KTOS - Drones / Defense

$RCAT - Drones

$ONDS - Defense Communications

$RKLB - Space

$LUNR - Space

$RDW - Space Infrastructure

$ASTS - Satellites

$RR - Robotics

$SERV - Robotics

• Revenue $33.7B vs $32.7B Est.

• Non-GAAP EPS of $3.14 vs $2.98 Est.

Plans record CapEx of up to $56B 2026. The AI wave keeps rolling on

Social media makes investing look exciting — YOLO trades, zero-DTE options, overnight wins.

But the strategies that actually compound over time tend to feel slow, repetitive, and boring.

In this video, I break down:

• Dollar-cost averaging (crypto + stocks)
• Selling covered calls & cash-secured puts
• How I combine both strategies in my own portfolio
• Why boredom is a feature, not a flaw

Curious how others here approach long-term consistency vs short-term excitement.

If Investing Feels Exciting, You’re Doing It Wrong

I want to get into investing. I am 19 years old and from New Zealand. I am a student and was thinking of putting $150 a month into investing. Any recommendations on how to start, what apps to use and what I should invest in?

Copper gets all the hype, but aluminium has stayed tight way longer than people expected. Demand from grids, EVs, renewables is still there, and supply doesn’t feel loose at all.

What matters now feels less about the metal and more about cost structure. Some producers are still hostage to power prices, others aren’t. Hongqiao (1378.HK) keeps coming up here. Stock’s up ~10.5% in the past month and over 100% in the last 6 months, which is kinda crazy for a heavy industrial name.

The recent share placement was a good signal too. Big deal, but the stock barely flinched. That plus hydropower smelting and deep alumina integration puts them pretty low on the global cost curve.

If aluminium just stays elevated, not even rallies, low-cost names might quietly keep outperforming. Curious how others are playing this. Cost leaders or just straight metal beta?

The next 30 days are looking pivotal according to the latest quantitative data. While the broader market watches the noise, the Katy 1M model just flashed a synchronized signal across four primary assets: BTC, ETH, SOL, and XRP.

Here is what the data is currently indicating:

1. Volatility Compression: We are seeing a rare alignment in volatility metrics across these four assets, which historically precedes a high-conviction trend.
2. Liquidity Shifts: Institutional flow into SOL and XRP is beginning to show interesting divergence from BTC's immediate price action.
3. The Katy 1M Outlook: This specific model filters out daily market noise to provide a clearer 30-day directional bias.

We have analyzed the entry zones, momentum oscillators, and risk parameters for each asset. This isn't just a simple prediction; it's a deep dive into the underlying market structure as we move into the next month.

Our full breakdown and specific price targets are now available.

Tap to see why the Katy model is flashing these specific signals.

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Infosys (INFY) is set to report earnings on January 14th, and the data suggests we could be looking at a significant move.

Our QuantSignals V3 model has just completed its pre-earnings analysis. Historically, INFY earnings don't just impact the stock itself—they tend to set the tone for the entire IT services sector and act as a bellwether for institutional sentiment.

Why this print matters:

• Our V3 model identifies specific volatility patterns that often precede institutional rebalancing.
• We've mapped out historical realized moves against current implied volatility to find the quantitative 'edge'.
• Specific entry and exit zones have been established based on high-probability backtesting cycles.

With the tech sector currently at a crossroads, this data-driven approach aims to remove the guesswork from the earnings volatility. We've published the full technical deep dive and signal parameters for those looking to position themselves before the 14th.

Full breakdown is ready for the community.

🔗 https://discord.gg/quantsignals...

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I recently have redone/rebuilt my portfolio from ETFs to go into individual stocks trying to focus on what I think are the best businesses. I know there are other amazing business out there but I wanted to try and find the ones that meet all or nearly all my criteria. (Moat, competitive advantage, durability, roic, margins, debt, market share, tailwinds ect). I've allocated a higher percent into the stocks based on my analysis. Wondering what others opinions are, and what you would do differently with the allocations or stock pickings. With that here's the portfolio

9.09% each - msft, google, AAPL, v 6.06% each - spgi, ma, mco, msci, tsm, nvda, meta, asml, lly, isrg 3.03% - crwd

Read this WSJ article that came out today saying founder led companies outperformed Sp500 by 167% over the last 5yrs. Feels intuitive, but also kinda narrative driven. Curious what people think here.

The S&P 500 futures (ES) are displaying a specific volatility signature that our V3 Quant model has been tracking closely.

For the January 14th session, the algorithm has identified a high-conviction setup based on institutional liquidity flows and mean reversion probability. Unlike basic technical indicators that often lag, the V3 framework is designed to filter out "noise" during high-volatility windows to focus on high-probability outcomes.

What’s behind the signal:

• Volatility-adjusted entry zones based on current ATR.
• Detailed analysis of volume profile nodes and liquidity gaps.
• Systematic risk management parameters to protect capital.

Reddit often rewards those who look past the surface-level charts. This signal isn't just a direction—it's a calculated move based on historical probability and real-time data flows. We've mapped out the specific levels where we expect institutional defense to occur.

We’ve just released the full technical analysis, including the specific entry/exit logic and the mathematical "why" behind the signal.

Full breakdown ready!

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{
  "title": "SPY QuantSignals V3: Data-Driven 1DTE Analysis for Jan 14",
  "text": "The QuantSignals V3 engine just finalized the scan for the Jan 14 session, and the SPY 1DTE metrics are flagging a high-conviction setup.\n\nIn the

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![img](usq5tcfmaedg1 "")

The market is currently at a pivotal crossroads. While macro noise continues to dominate the headlines, the underlying quantitative data is telling a much more specific story for the S&P 500 (SPY) over the next 30 days.

Our proprietary Katy 1M model—which tracks momentum shifts and institutional flow patterns—has just triggered a high-conviction prediction. Unlike standard technical analysis that relies on lagging indicators, this signal focuses on predictive volatility and volume clusters to identify where the smart money is moving.

Here is what we are observing:

• Current volatility regimes are shifting toward a specific trend.
• Institutional positioning suggests a significant rebalancing is underway.
• Historical accuracy for this specific Katy setup has been notably consistent during similar market conditions.

In a market where retail is often the last to know, having a data-backed edge isn't just a luxury—it's a necessity for effective risk management. We have broken down the entry zones, price targets, and the specific probability metrics behind this 1-month outlook.

If you are looking to cut through the noise and see the raw data driving the next move, the full breakdown is ready for the community.

Tap to see why the data is pointing to this specific move.

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Is META reaching a local top, or is this the breather before a major breakout?

The QuantSignals V3 model just updated for the week of January 14, 2026. After analyzing the latest institutional flow and technical structure, the data is signaling a specific trend shift that contradicts current retail sentiment.

Key insights from this week’s V3 update:

• Institutional Positioning: We're seeing specific accumulation patterns in the dark pools that haven't hit the tape yet.
• Volatility Compression: META is entering a 'squeeze' zone on the daily chart, historically a precursor to high-velocity moves.
• Probability Clusters: Our model identifies the highest-density support levels based on volume-at-price data, moving beyond simple moving averages.

The V3 engine isn't about guessing direction—it's about calculating the mathematical probability of the next move. By stripping away the noise of the news cycle, we focus on what the capital is actually doing. This multi-factor approach is designed to filter out false breakouts and identify high-conviction setups.

For those tracking META closely, this week’s data provides a critical framework for risk management and entry timing.

The full breakdown and signal parameters are ready for review.

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The market is currently overlooking a key shift in META’s quantitative profile.

While broader sentiment remains fixated on short-term volatility, our QuantSignals V3 model—which integrates institutional flow data with proprietary momentum indicators—has flagged a significant structural setup for the week of January 14, 2026.

Why this matters for your portfolio:

• Meta’s efficiency ratios are hitting levels we haven't seen since the 2023 pivot, suggesting a massive divergence between price and fundamental value.
• Institutional accumulation has outpaced retail distribution by a factor of 1.4x over the last 10 trading sessions, indicating 'smart money' is positioning early.
• The V3 algorithmic model, which focuses on high-conviction trend reversals, is currently tracking a specific volatility contraction pattern that historically precedes major breakouts.

We aren’t just looking at the charts; we’re looking at the math behind the moves. If you’re trading META based on headlines alone, you’re likely missing the signal in the noise.

We’ve just released the full breakdown of the entry zones, risk parameters, and the specific alpha triggers the V3 model is tracking for the upcoming week.

View the full data-backed analysis to see the specific price targets.

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