Z
Zillow Group, Inc. Class C Capital Stock
stock NASDAQ

Gen Z has been tik tok pilled into loving CCP slop

What I find helpful for modeling the broader markets is look at longterm trend, short term trend, Z score for longterm trend and Z score for short term trend. Much of the flow in and out really revolves around the Z scores. Money doesn't flow in until things are properly oversold at Z=-2. likewise money moving out at z=+2 and trend intract as long as it stays roughly in thoose ranges. If breaks support at z=-2 then bearish regime and +2 bullish regime. Individual stocks are obviously different and what I find helpful there is the price change in response to order flow.

The title speaks for itself. When developing strategies, especially for smaller accounts, sometimes I just talk it out with AI. With the current trend I've been noticing with crypto and the derivates market I thought it would be interesting to get a roast session on why this strategy is trash. please feel free to go ahead
"Crypto Statistical Arbitrage
A Simple Guide to Pairs Trading in Crypto
January 2026
1. What Is Statistical Arbitrage?
Statistical arbitrage (or "stat arb") is a trading strategy that profits from temporary price differences between related assets. Instead of betting on whether crypto goes up or down, you bet on the 
relationship between two assets returning to normal.
Think of it like this: If two things usually move together and suddenly one jumps ahead while the other lags behind, eventually they tend to meet back in the middle.
2. The Core Idea: A Simple Analogy
Imagine two street vendors who both sell rain gear. One sells umbrellas, the other sells raincoats. When it rains, both see their sales go up together. Their businesses are correlated.
Now imagine one day the umbrella vendor has a viral TikTok and sales spike, but raincoat sales stay normal. What do you do?
Option A: Bet umbrella sales will fall back to normal
Option B: Bet raincoat sales will catch up
Option C: Do BOTH at once (this is stat arb!)
By betting on both sides, you don't care which one happens — you just need the relationship to normalize.
3. How It Works With Crypto
Step 1: Find Related Pairs
Many cryptocurrencies move together. When BTC goes up, most altcoins follow. We look for pairs that have a stable relationship over time.
Step 2: Wait for the Spread to Get "Weird"
We measure how far apart the two assets are from their normal relationship using something called a Z-score. This is just a fancy way of measuring "how many standard deviations from normal."
Z-score = 0: Normal relationship
Z-score = +2: One asset is unusually expensive relative to the other
Z-score = -2: One asset is unusually cheap relative to the other
Step 3: Trade When Z-score Hits ±2
When the Z-score gets extreme (typically beyond ±2), we enter a trade:
If Z = +2: Short the expensive one, Long the cheap one
If Z = -2: Long the expensive one, Short the cheap one
Step 4: Exit When Z-score Returns to 0
When the relationship normalizes (Z-score crosses 0), we close both positions. We've captured the "mean reversion."
4. Understanding Crypto Derivatives Beta
Why do all crypto charts look the same? If you've ever noticed that BTC, ETH, ADA, SOL, and XRP charts look nearly identical, you're seeing beta in action.
What Is Beta?
Beta measures how much an asset moves relative to a benchmark. In crypto, we use BTC as the benchmark (beta = 1.0). If an altcoin has beta = 2.0, it means when BTC moves 1%, that altcoin typically moves 2%.
Crypto Beta Values (Empirical)
Based on actual market data, here are the beta values for major cryptocurrencies relative to BTC:
Asset
Beta to BTC
When BTC Moves +1%
BTC
1.00x
BTC moves +1.00% (baseline)
ETH
1.98x
ETH moves +1.98% (nearly 2x)
ADA
2.20x
ADA moves +2.20% (highest beta)
XRP
1.77x
XRP moves +1.77%
SOL
1.55x
SOL moves +1.55%
What This Means for Stat Arb
When BTC moves 3%, here's what we'd expect each asset to move:
ETH: +5.94% (3% × 1.98)
ADA: +6.60% (3% × 2.20)
XRP: +5.31% (3% × 1.77)
SOL: +4.65% (3% × 1.55)
If ADA only moves +4% instead of the expected +6.6%, that's a deviation from beta — exactly what stat arb looks for.
Effective Multiplier (Leverage × Beta)
When trading crypto derivatives with leverage, the real "bang for your buck" is leverage × beta. This is the effective multiplier:
Asset
Leverage
Beta
Eff. Multiplier
Rank
ETH
10x
1.98x
19.8x
\#1 Best
ADA
5x
2.20x
11.0x
\#2
BTC
10x
1.00x
10.0x
\#3
XRP
5x
1.77x
8.85x
\#4
SOL
5x
1.55x
7.75x
\#5 Worst
Insights: Despite ADA having the highest beta (2.20x), it only has 5x leverage, so ETH with 10x leverage and 1.98x beta is actually the most capital-efficient asset for derivatives trading.
Why ADA/XRP makes a good pair: Both are high-beta altcoins (2.20x and 1.77x) with similar investor profiles. When one spikes on retail FOMO, the other tends to catch up. This creates tradeable mean-reversion opportunities.
5. Why Trade Both Sides?
This is the magic of stat arb: You don't care if crypto goes up or down.
Long one asset (betting it goes up)
Short the other (betting it goes down)
If the whole market drops 10%, both positions lose value — but one goes up relative to the other. Your profit comes from the relationship changing, not the overall direction.
This is called being "market neutral" — you've hedged out the market risk and are only betting on the spread.
6. Real Backtest Results
We tested 10 different crypto pairs over 365 days (Jan 2025 - Jan 2026) using 3x leverage and 20% position sizing:
Pair
Return
Sharpe
Max DD
Win %
Trades
ADA/XRP
\+68.99%
2.21
\-17.13%
64.7%
17
BTC/ETH
\+34.11%
1.21
\-30.90%
47.1%
17
ETH/ADA
\-9.34%
0.17
\-20.32%
50.0%
14
Other 7 pairs
\-10% to -40%
<0.5
Various
35-50%
\-
Findings: Only 2 out of 10 pairs were profitable. Pair selection matters enormously.
7. ADA/XRP 
Metric
Value
Initial Capital
$1,000.00
Final Value
$1,689.86
Total Return
\+68.99%
Number of Trades
17
Win Rate
64.7%
Profit Factor
2.55 (wins are 2.55x losses)
Average Trade P/L
\+$42.80
Best Trade
\+$275.85
Worst Trade
\-$270.14
Max Drawdown
\-17.13%
Sharpe Ratio
2.21
8. Why Win Rate Doesn't Matter
Most people obsess over win rate. "I want a strategy that wins 80% of the time!" But win rate alone is meaningless. What matters is expectancy.
The Expectancy Formula
Expectancy = (Win Rate × Average Win) - (Loss Rate × Average Loss)
A Counter-Intuitive Example
Imagine a strategy with only 10% win rate. Sounds terrible, right? Let's see:
100 trades total
90 losers at -$1 each = -$90
10 winners at +$100 each = +$1,000
Total P/L: +$910 despite 90% of trades losing!
Expectancy per trade: (0.10 × $100) - (0.90 × $1) = $10 - $0.90 = +$9.10
Most people wouldn't trade this because "90% of trades lose!" But it's a winning system.
9. Why ADA/XRP Works (The Explainability Test)
Having good backtest numbers isn't enough. You need to be able to explain WHY the edge exists. Otherwise it might just be luck (curve fitting).
For ADA/XRP, we can explain the edge:
Same investor base: Both are retail-favorite "hope coins" bought by similar traders
Similar risk profile: Both are speculative altcoins with high volatility
Liquidity rotation: When one pumps, profits often flow to the other
Beta clustering: Both have high beta to BTC (\~2x), so they move together
FOMO dynamics: When retail FOMOs into one, the other often catches sympathy bids
When ADA spikes on retail FOMO and XRP doesn't, there's pressure for XRP to catch up OR ADA to fade. Either way, the spread normalizes.
10. Important Caveats
Walk-Forward Validation
We tested whether these results hold on data the model hadn't seen. The reality check:
Training period: +47.46% return, Sharpe 1.84
Testing period: +6.48% return, Sharpe 1.15
Degradation: 74% (significant overfitting detected)
Realistic Expectations
Expected Annual Return: 15-30% (not 69%)
Expected Sharpe: 0.6-1.2 (not 2.21)
Expected Max Drawdown: 25-35%
No Cointegration
None of our pairs showed true statistical cointegration (p-value for ADA/XRP was 0.96). This means we're trading correlation, not guaranteed mean reversion. Higher risk than "pure" stat arb.
Regime Change Risk
What if the ADA/XRP relationship breaks down? Maybe XRP wins its lawsuit and decouples. Maybe ADA gets a huge DeFi upgrade. The historical relationship could break.
11. The Bottom Line
Statistical arbitrage in crypto offers:
A way to profit that doesn't depend on "crypto going up"
Positive expectancy with an explainable edge
Capital efficiency through leverage
Market-neutral exposure (theoretically, but requires discipline)
But requires:
Understanding that backtests overstate performance
Discipline to stick with it through drawdowns
Acceptance that the edge can disappear
"Expectancy matters, not win rate. But expectancy without explanation is just curve-fitting."
Research conducted January 2026
Data: Yahoo Finance | Backtest: VectorBT Pro | Analysis: Python"

A chief goal of MC is to avoid a situation where you are tuning to the noise rather than the signal. This alternative does the same thing by ensuring the optimum (or at least good) setting for one of your parameters is not overly sensitive to the setting of another.
A1. Varying parameters does generate new return paths because varying parameters will change entry and exit signals.
A2. I never said that one should not test in different regimes. The special rule is another way of saying "A change in market regime \_never\_ counts as a Type C parameter because it will virtually always affect optimal parameters." One should analyze behavior across long time periods that include changes in market regime, but that testing is separate and more aligned to absolute performance rather than relative performance \[how one set of parameters compares to another.\]
A3. In this framework varying a lot of A and C choices is \*\*not\*\* a huge number of experiments, it is \_one\_ experiment. This framework is not about testing (or finding) a single set of parameters to validate. This framework is about testing the very system itself---if your system is such that varying A and C leads to substantial movement in optimum/good values of the type B parameters, then the entire sysem is suspect and should be reconsidered. If the rationale behind your choice of indicators and overarching system setup indicates that the values of parameters X & Y should not impact what "good" settings are for parameter Q, and then the test shows that is wrong \[that "good" settings for Q depend a lot on parameter X & Y\], then it calls into question the rationale behind the system and indicates that Q is a parameter susceptible to noise.
A4. My reference to trying out the same system on different tickers was to validate the rationale behind the system... so clearly it could not have been a suggestion to choose a ticker based on the results. If the ratonale behind your system indicates that it should work similarly for X, Y, and Z and parameters optimized for X (without use of data from Y or Z) perform well when applied to Y & Z, then that is a material validation of the system.
This last point even holds if X, Y, and Z are viewed as being strongly correlated. Even stocks that are strongly correlated in the large vary qutie a bit in their noise, which is exactly what you want when trying to confirm your system is robust against fitting to noise. Sure, WM and RSG are very correlated mathematically, \*\*but the differences in their tick-by-tick prices is going to be far higher than the perturbation you would get from a MC simulation.\*\* In backtests on WM/RSG or V/MA in my system, the correlation in system responses (net gains, which ticks which are held, entry & exit) are surprisingly low.

as a Gen Z'r, that's how I'm viewing it as well. As frustrating as it is, I can't bet all my chips on SS still being around by the time I return.

Social Security for Gen Z

Isn’t Gen Z also the children of boomers and Gen X, so then Gen Z hates themselves? 
Not to mention Gen Z hasn’t really had the spending power to access elite Amex cards…

Where does he think Gen Z came from

We really need to stop allowing Gen Z kids like OP from being able to post the dumbest takes here lmao

Yeah AMEX is only missing the poor Gen Z. And poor people don’t affect the K shaped economy I think

>Gen Z, who sees Boomers and their offspring as borderline elitist scum
*Trust me bro*

Die Überschussbeteiligung hat sich bei mir bisher erhöht. Tendenziell erhöht sie sich, wenn die Zinsen (Z.B. Euribor) hochgehen und reduziert sich, wenn sie sinken, allerdings deutlich langsamer als diese. D.h. Die Überschussbeteiligung von Lebensversicherungen ist heute etwas höher als vor 5 Jahren und viel niedriger als vor 30 Jahren. Die Solvenzquote kann dir ein wenig etwas darüber sagen, ob die Versicherer sich ihre Überschussbeteiligung leisten können.

Kommt bei 28 days/weeks/years und World War Z schon ganz hin. Die klassischen Romero Zombiefilme versuchen es ja so zu erklären, dass irgendwelche Kulturgruppen ihre Toten nicht hergeben wollen. Hab zwar keine Ahnung von Pharma, aber Zombies sind mein Steckenpferd.

The stock has been nearly halved from its highs, battered by slowing U.S. spending and execution missteps. Further complicating things is the boardroom battle between Chip Wilson, the current board, and the new activist investor Elliott Management.
On paper, LULU looks like a slam-dunk value play. It's a business generating 39% ROIC**,** a balance sheet with $1 billion in cash and zero debt, and a fast growing International business that is offsetting the slowing North American business.
So, is this a mismanaged compounder ripe for an activist turnaround, or a classic value trap?
Despite the cheap price, there are aspects that screaming "Value Trap."
1. The Two-Front War: LULU is being flanked on both sides. Alo Yoga is winning the "cool" war for Gen Z women (studio-to-street fashion), and Vuori is besieging the men’s segment with a "California Coastal" aesthetic that is eating into LULU's ABC pant dominance.
2. Dupe Culture: When $25 Amazon/Costco leggings feel 95% similar to $98 Aligns, the IP moat dissolves. "Dupe" culture is commoditizing their innovation.
3. Execution Failures: We are seeing unforced errors. The recent "Get Low" recall (sheerness issues) in Jan 2026 echoes the 2013 Luon crisis. This suggests a breakdown in quality control.
4. Inventory Bloat: Inventory grew 11% while sales grew only 7% - a red flag that suggests they are misreading demand and will need to mark down product, hurting margins.
5. Declining ROIIC: ROIIC is turning negative. This, plus deciling operating margins, suggests their moat is eroding.
6. Lease Liabilities: While true that there is no long term debt, LULU has \~ $1.4B in lease liabilities that create high fixed costs.
LULU highlights the difference between "undervalued" and "high quality." While the stock is statistically cheap, there is evidence that the moat is under siege. Yes, the international business is booming, although their cultural relevance is fading in their core North American market.
It is cheap, although probably not a suitable long term hold as it may eventually go the way of Under Armour.
For someone looking for a "reversion to the mean" trade with an exit when valuation rerates, it's probably reasonable. OTOH, the days of being a "compounder" are probably in the rear view mirror.
Full analysis with in depth valuation posted here - [https://thepursuitofcompounding.substack.com/p/lululemon-athletica-mismanaged-compounder?r=xy3ae](https://thepursuitofcompounding.substack.com/p/lululemon-athletica-mismanaged-compounder?r=xy3ae)

President Al Z. Heimer

*I would like to preface this by saying I had attempted to post this on or around December 31, 2025 but was unable due to account newness.*
*As a result I'm posting this now, despite not being as fresh-to-market news, to ensure those who are looking into FinTech in the current landscape are aware of the risks present.*
\-------
Dave Inc. (DAVE) has recently received a significant threat to its business model as of December 30, 2025.
\***Judicial and regulatory bodies are beginning  to clamp down on predatory FinTech practices which are being masked as voluntary contributions, charitable tips, and fees & charges.**\*
\*\***The small news that skipped headlines (but with a big cascade risk) is the Baltimore v Dave Inc lawsuit filed December 30, 2025**\*\*
If the Baltimore City lawsuit (filed December 30, 2025) successfully argues that these charges are "finance charges" under 12 C.F.R. § 1026.4 (Regulation Z), Dave’s effective APR (often exceeding 400%) would violate Maryland’s 33% usury cap and significantly impact Dave's bottom line, profitability and business model.
This follows the precedent in District of Columbia v. EarnIn (Nov. 2024), where the DC Attorney General sued a near-identical provider for charging fees that yielded a 300% APR, rejecting the defense that these payments were voluntary "donations." 
\**This led to the case law and precedent referred to as \*EarnIn doctrine\* that donations are not voluntary, and fees are part of the loan*.\*
\**Critically*\* the Consumer Financial Protection Bureau's (CFPB) Regulatory integration of the doctrine into the 2024 Interpretive Rule. This regulation has been refined in \*\*December 2025\*\* enforcing the interpretation that "tips" and "expedited delivery fees" are considered "credit" subject to the Truth in Lending Act (TILA) if they are part and parcel of the extension of funds.
DAVE and other FinTech/BNPL/Advance lenders rely on state Safe Harbor laws to bypass APR limits currently. 
Other lenders are also getting rapidly hit by agencies (California DFPI v OppFi, Baltimore v MoneyLion, 2025, New York AG v MoneyLion, CFPB v MoneyLion, DC v EarnIn 2025, FTC v CleoAI, Rubin v EarnIn, Aug 2025, and the number of lawsuits are increasing)
The problem? 
\*\***More Precedents!\***\*
City of Miami v. Gonzalez (Fla. Dist. Ct. App. 2025), which went to Court of Appeals final ruling established that municipal charters can empower cities to enforce local consumer protections even where state laws are permissive, effectively allowing Baltimore to and other cities to ignore state level permission laws \*AND apply the EarnIn Doctrine\*. 
As a double whammy, the DOJ is naming CEO Jason Wilk as a personal defendant in its amended complaint (Dec. 2025), which is almost a replica of the FTC v Brigit 2024 case, where Brigit had to pay a $18 million settlement for deceptive fee-harvesting interfaces \*\**AND a permanent injunction*\*\*. CleoAI also had to settle a case with conditions against the FTC for $17M. 
On an ethical and legal front, recent revelations of exploiting "charitable" nudges to the bottom line $149 million tip revenue, Dave is increasingly exposed to a multi-front wave of municipal and federal litigation, and also souring retail & ethical sentiment.
If these revenue drivers are deemed illegal interest, Dave loses its primary margin engine. Its core revenue generator turns into an unlicensed, high-interest loan.
A single 40k share institutional sell block on Dec 29 over a holiday trading period immediately following the news, is a warning signal investors might want to be aware of if currently holding a DAVE position. 
While some risk is built into the current price, a bigger downside risk exists if multiple city & state jurisdictions follow Baltimore's lead - possibility of numerous settlements, restrictions and injunctions can potentially severely cripple the business model.
\**Disclaimer: Previous Dave bull here. I post this to help ensure I give a transparent take on any stocks I have held or hold, especially when I see big regulatory headwinds, as I don't want others to get burnt on a stock. I have exited DAVE due to this increasing risk. Not AI*\*

Du musst immer daran denken, wem eine Reform schaden würde und wie sich das auf das Wahlverhalten auswirkt.
Explodierer haben haben im Vergleich relativ wenig Kapital in Aktien und ETFs dafür ne Menge Betongold und Geld auf dem Sparbuch.
Generation X, Y, Z dagegen vertrauen heutzutage eher auf ETFs und Aktien.
Bei wem kann man sich was holen ohne zu riskieren bei der nächsten Wahl abgestraft zu werden.

I'm late to the thread but I think you could be onto something. Fundamentally the company is well run, financially speaking.
They may not have the best ideas (tech glasses) but they have a good product. I think the main thing is fad. They aren't that cool right now, Instagram stories came around and ate their lunch.
But I could see Gen Z trying their hand at Snap, as it was a littke before their time and never used when it was super popular. So they could get rotate from Insta to Snap. I wouldn't invest quite yet though. I'd wanna see it pop more culturally.

During the early days of the spider sentience war of '31, Elon the 3rd known in those days as the Great Z first activated the METAMind in order to probe deepspace for the last remaining silver deposits.

Option 1: FTSE All-World.
Warum? Du bekommst ein diversifiziertes Paket, das historisch eine gute Performance hatte. Du legst es an und lässt es einfach liegen. Damit lernst du NICHT ZU HANDELN. Das ist die härteste Disziplin.
Option 2: 60:40 FTSE All World und 2-3 Einzelaktien (zum Beispiel 1x Tech + 1x Rüstung).
Warum? Du verstehst und erkennst wie unterschiedlich sich ein diversifiziertes Produkt im Gegensatz zu Einzelpositionen entwickelt. Du erkennst wie sensitiv Einzelpositionen (Z.B. Rüstung) auf das aktuelle Weltgeschehen reagieren können und vor allem wie du emotional darauf reagierst (sehr wichtiges learning). Es erfordert von dir aber noch mehr Disziplin und du findest dich, wenn’s mal nicht super läuft, schneller in einer Situation wieder, in der du am liebsten alles verkaufen möchtest.
Ich würde dir zu Option 2 raten. Du bist jung, hast erstmal (objektiv gesehen) nicht viel zu verlieren und im Zentrum sollte der Lerneffekt stehen. Wenn du dann nach Ausbildung/Studium ernsthaft investierst, bist du vorbereitet und kannst die für dich beste Strategie wählen.
„Time in the market beats timing in the market.“