D.C., MD

Market addict trying to find hidden gems capable of superperformance. I also do some medicine. Gotta catch‘em all, superstocks ! Dave Catchem 🤘🏻

[jack schwager @jackschwager]

I was making progress, and as long as I saw improvement-no matter how small-I knew I would eventually get to where I wanted to be as a trader. - Lukas Frohlich @TheShortBear 26/n https://t.co/b9PLYapuJD

[D.C., MD @superstock_guy]

@realSharat Me too

[D.C., MD @superstock_guy]

@PradeepBonde Took a look at the both again and totally get what you mean.

[D.C., MD @superstock_guy]

@PradeepBonde $MRVL same action but over 21 dema. Why did you choose $ARM ?

[D.C., MD @superstock_guy]

@jfsrev $NUAI still has a killer short setup around 7$, it may need a little more time or some kind of good catalyst to blast through that resistance. Not the first time it got rejected around the same level. Do you see the current exponential volume increase as institutional interest ?

[D.C., MD @superstock_guy]

@PradeepBonde Ahahahaha, this one was amazing 😂

[J Law @JLawStock]

The next big AI trade won’t come from chasing the same names everyone is already crowded into.

It will come from spotting the next bottleneck before the market does.

After $NVDA, $ARM, and $MRVL have already made their explosive moves, everyone is asking the same question:

Which stock could be next?🚀

In my new YouTube video, I break the AI industry into a simple 3️⃣-layer framework — and explain why I’m now paying close attention to Layer2️⃣: the “hidden middle layer” between AI hardware and end-user applications.

This is where AI starts moving from hardware hype to real enterprise adoption — and where the next wave of capital could start crowding in.

If you still want AI exposure but feel late to the first wave, this framework gives you a cleaner map of where the next explosive opportunity may appear.

Watch the full breakdown on YouTube — before the next AI trade shows up on everyone’s radar.🚨

Check out the video here👇
https://t.co/XTx47cGpCN

[Market Rebellion @RebellioMarket]

Market Wizard Linda Raschke’s 12 Technical Trading Rules:
1. Buy the first pullback after a new high. Sell the first rally after a new low.

2. Afternoon strength or weakness should have follow through the next day.

3. The best trading reversals occur in the morning, not the afternoon.

4. The larger the market gaps, the greater the odds of continuation and a trend.

5. The way the market trades around the previous day’s high or low is a good indicator of the market’s technical strength or weakness.

6. The previous day’s high and low are two very important “pivot” points, for this was the definitive point where buyers or sellers came in the day before. Look for the market to either test and reverse off these points, or push through and show signs of continuation.

7. The last hour often tells the truth about how strong a trend truly is. “Smart” money shows their hand in the last hour, continuing to mark positions in their favor. As long as a market is having consecutive strong closes, look for up-trend to continue. The up trend is most likely to end when there is a morning rally first, followed by a weak close.

8. High volume on the close implies continuity the next morning in the direction of the last half-hour. In a strongly trending market, look for resumption of the trend in the last hour.

9. The first hour’s range establishes the framework for the rest of the trading day.

10. A greater percentage of the day’s range occurs in the first hour then was the case in the past, and thus it has become increasingly important to trade aggressively if there are early signs of a strong trend for the day.

11. There are four basic principles of price behavior which have held up over time. Confidence that a type of price action is a true principle is what allows a trader to develop a systematic approach.

[D.C., MD @superstock_guy]

I think you nailed it with your entries on 9. and 12. if I remember correctly. If you caught the consolidation low in some names you would basically just need to sit it through now. If you were to initiate new positions now, what would you look for ? I Reduced trading frequency a lot and playing only A+ plays now given I missed the pullback low. Now entering when in the range could just chop me up.

[D.C., MD @superstock_guy]

@Scot1andT Absolutely. I know I feel uncomfortable buying in strength so I stick to UnRs and pullbacks. Occasionally take a nice EP but watch for a controlled pullback on the 5 min or UnR of a significant level where the buyers are ready to defend hard.

[D.C., MD @superstock_guy]

@TheOneLanceB @katsuxbt Thanks Lance, means a lot! ❤️

[D.C., MD @superstock_guy]

@PradeepBonde Best learning method. I have a few 7 and 8 fig traders as friends and they can be pretty brutal when I traded like crap. Btw are you coming to Germany again in some time?

[D.C., MD @superstock_guy]

Well there aren’t many 9 fig traders XD Btw yday finished your chapter in the Wizards. Others may be smarter, have more starting capital, more time, but not many of them are more obsessed. I stopped pricing in the failure already, it‘s literally impossible for me to fail, only thing now is how much time will I need to reach the 8 figs.

[D.C., MD @superstock_guy]

@Scot1andT @PradeepBonde Which camp was yours when you started?

[stockbee @PradeepBonde]

Never stop developing new edges. More you expand your playbook better it. Edges evolve, some go through cycles, some disappear, so a constant search for new edges is a must for longevity in this business,

[D.C., MD @superstock_guy]

@PradeepBonde Coming to Germany again soon ? Missed the one in Frankfurt last year sadly

[SAKATAS HOMMA 📈 @SakatasHomma]

Is this Stock over-extended?

PARAS

One concept that has shaped my selling strategy over the years is identifying overextended stocks.

Most traders define overextension as a stock being "too far" above a moving average.

I think that's incomplete.

A 10% extension may be extreme for a slow-moving large cap.

The same 10% extension may be completely normal for a volatile small cap.

The better question is:

How extended is the stock relative to its own volatility?

That's where ATR comes in.

For years, trading Indian microcaps and smallcaps, I observed that many stocks become vulnerable to pullbacks once they reach roughly 6X ATR above the 20SMA.

This wasn't based on a backtest.

It was based on thousands of chart observations and real-money trading experience.

Recently, I came across fascinating research from Nigel at TheStrat Lab.

He analyzed:

• 5+ years of data
• ~2,700 US stocks
• Millions of daily candles
His findings:
• 1σ ≈ 2.5X ATR above the 50SMA
• 2σ ≈ 5X ATR above the 50SMA
• 3σ ≈ 7.5-8X ATR above the 50SMA

In other words:

A stock trading 7.5-8X ATR above its 50SMA is operating in statistically rare territory.
Not certainty.
Probability.

And that's an important distinction.

My observations come from Indian markets.

The data comes from US markets.

Different universes.

Yet both point toward the same underlying truth:

When price stretches too far relative to its own volatility, the odds of mean reversion begin to rise.

A current example is Paras Defence.

As of today's close, it is roughly 6X ATR extended from 20-SMA, on my framework.

Does that mean it will (certainty) reverse next week?

Absolutely not.

Many monster winners remain extended far longer than traders expect.

AMD did.

HOOD did.

Countless Indian momentum stocks have done the same.

But when a stock enters these zones, the reward-to-risk equation starts changing.

That's why I track extension.

Not to predict tops.

Not to short strength.

Not to be the smartest guy in the room.

But to:

• Sell into strength
• Protect profits when probabilities begin shifting

The goal isn't calling the exact top.

The goal is recognizing when the rubber band is already stretched.

For those interested, I've built an indicator that automatically plots a yellow dot whenever a stock reaches my overextended threshold.

I will share in the comments below:
1. The Yellow dot indicator.
2. Detailed explanation on "over-extendedness"
3. Nigel's (@StratLaboratory ) statistical analysis of @jfsrev 's extended rule.

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