Dinesh

Just another stock market trader

[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,

[stockbee @PradeepBonde]

Copy shamelessly setups, scans, processes that have worked for someone else.

[Lunix Twin @LunixTwin]

Mark Cuban explains exactly how he would turn a sales job into his own business in under six months

"I am really, really, really good at sales. I'm gonna find a sales job because I already know that if I'm onto my last $500 and all I have is a phone, I am going to get that job and I'm gonna learn more about that industry than anybody on the planet."

"And I'm gonna set a commission as high as I possibly can. And three months in, when I've demonstrated that I am the best salesperson in the history of that company, I'm going to walk into my boss's office and I'm going to tell him or her, you're either going to pay me this amount of money to keep me or I'm going to start my own business selling this stuff."

"Everything always goes back to sales no matter what."

[stockbee @PradeepBonde]

The aha moment when you figure it out is priceless. Makes life so easy.

[Kevin Carpenter @kejca]

Mohnish Pabrai: "When I look at a CEO, I always try to find out — did they run a lemonade stand when they were twelve? Because if they didn't run the lemonade stand when they were twelve, they're not going to be that great at business at thirty."

"The little itty bitty lemonade stand has a lot of lessons." (h/t @myfirstmilpod)

[stockbee @PradeepBonde]

See my post
Study trader on Twitter who are killing it rather than reading book.
Study @Qullamaggie @RealSimpleAriel @InvestorsLive @jfsrev @FranVezz @mmonis @Lolomat64317383 @XpertPATrader @BornInvestor and similar kind of communities where practitioners show how it is done
This is not exhaustive list

https://t.co/5mH38zD0Lj

[stockbee @PradeepBonde]

You can do lot of back testing but I find easier to study popular newsletters and discords and popular twitter traders and study their setups and tactics and find a smarter or different way to do it.
They already have done the back test and hard work. I just shamelessly copy and improve.

[Capt. Erik Brandsen @Erik96754]

I spent the last few weeks going back in time studying @PradeepBonde TC2000 EP 9 million scan. If you were astute and committed you could have entered the top 100 winners on day 1 of their breakout. There is no better edge than that scan in my opinion.

[Suresh K @SureshKBN]

I don’t know. Looking back, I did the hard work, followed the routine, and kept showing up every day. But more than anything, I had this deep conviction that I would be successful one day.

Maybe life r god is just settling old dues now. Maybe all the rewards that a stammering, awkward kid couldn’t collect back then are finally arriving after decades of waiting.

[Suresh K @SureshKBN]

I was here from 2010.

Life was cool when I was not known, or when I had less than 500 followers.

I started posting more after quitting my job three years back, and even more after my knee ACL surgery.

I did every mistake a new investor does.

You name it, I might have done it.

Bought stocks from Moneycontrol discussion boards 20 years ago without understanding the business or risks.

After some initial success, got false confidence, took a ₹2 lakh personal loan, invested it, and burned almost everything.

Averaged down thinking price has to come back.

Bought penny stocks and low market-cap names thinking they will rise fast.

Followed TV recommendations.

Every stupid mistake a beginner investor makes, I have done it.

In Telugu there is a line:

“Bhogi kaanivaadu Yogi kaaledu.”

One who has not gone through indulgence, mistakes, burns and temptations cannot become wise like a yogi.

So when I say something today, it is not theory.

It is burn marks speaking.

--------
Other mistakes I did as a new investor:

Buying just because the stock had fallen 50%, thinking it had become cheap.

Confusing low price with cheap valuation ₹10 stock looked cheaper than ₹1,000 stock.

Looking only at profits, not cash flow, debt, pledging, dilution or promoter quality.

Selling winners too early and holding losers forever.

Thinking every operator-driven move is “smart money accumulation.”

Believing every turnaround story without checking whether the balance sheet can survive.

Buying because some big investor entered, without understanding their time horizon or position size.

Taking allocation too big in stocks I did not understand properly.

Not respecting liquidity — easy to enter, impossible to exit.

Getting emotionally attached to stocks and defending them like family members.

Mistaking bull market luck for personal skill.

Thinking more information means better decision-making.

Watching price every day but not watching business progress.

Ignoring opportunity cost holding dead stocks while better stocks kept moving.

Learning risk only after losing money.

[Dinesh @DineshTrader]

Volume Profiling.

[Suresh K @SureshKBN]

Nothing specific. Just read all the well-known books.

But the most important thing is not what book you read.

It is what exactly you want to learn.

I had almost 20% position in Apar Industries, based on FA and more importantly TA.

But the price action was erratic. I could not convince myself what was really happening.

So the real question became:

Who is holding the power inside the candle? Buyers or sellers?

That question pushed me into volume profiling. I learnt it almost overnight.

In markets, your questions are more important than my answers.

Answers only help for a day.

The right question changes the way you see the market forever.

[Suresh K @SureshKBN]

Watch fertilizer plants closely DEE Dev, JNK, L&T many mentioned in calls

Fertilizer capex revival, refinery/petrochemical ordering, and now the government’s coal gasification push
multiple stars seem to be aligning.

FY27 may not just be about one company’s execution; it could be about an entire industrial capex cycle opening up.

[Lone @lonextrades]

Qullamaggie on Becoming a Successful Trader: Start in Your Early 20s or 30s with No Responsibilities

“If you’re starting out trading, it’s a very hard thing, you know, becoming a successful trader. Most people that I know who started out trading and were successful, they started trading when they were in their 20s, somewhere in their thirties. Most of them were single and had no kids when they started out.

But once you’re profitable, it doesn’t matter because you don’t have to put in the same effort. Then it doesn’t matter if you have kids and family — you can make it work anyway once you’re profitable.

However, when you’re starting out, you better not have a lot of other commitments because it’s gonna be a very hard thing to try to learn trading if you have kids. Oh man, I wouldn’t have become a successful trader if I had kids when I started out. No way.”

[Anish Moonka @anishmoonka]

Winston Churchill fought his depression with bricks. He'd lay them for hours at his country home in Kent. He joined the bricklayers' union. And in 1921 he wrote about why it worked. It took psychology another 75 years to catch up.

He called his depression the "Black Dog." It followed him for decades. His method for fighting it back was as basic as it sounds: laying brick after brick, hour after hour.

Churchill spelled out his theory in a long essay for The Strand Magazine. People who think for a living, he wrote, can't fix a tired brain just by resting it. They have to use a different part of themselves. The part that moves the eyes and the hands. Woodworking, chemistry, bookbinding, bricklaying, painting. Anything that drags the body into a problem the mind can't solve by itself.

Modern psychology now calls this behavioral activation. It's one of the most-studied depression treatments out there. Depression sets a behavior trap. You feel bad, so you stop doing things, and doing less means less to feel good about. Feeling worse makes you do even less. The loop tightens until you can't breathe inside it.

Behavioral activation breaks the loop from the action side. You schedule the activity first, even when every part of you doesn't want to. Doing it produces small rewards: a wall gets straighter, a painting fills in, a messy room gets clean. Those small rewards slowly rewire the brain. Action comes first, and the feeling follows.

Researchers at the University of Washington put this to the test in 2006. They studied 241 adults with major depression and compared three treatments: behavioral activation, regular talk therapy, and antidepressants. For the people who were most severely depressed, behavioral activation matched the drugs. It beat the talk therapy. A 2014 review of more than 1,500 patients across 26 trials backed up the result.

Physical work like bricklaying does something extra on top of this. It crowds out rumination, the looping bad thoughts that grind people down during the worst stretches of depression. Bricklaying needs both hands and gives feedback brick by brick: each one is straight or crooked. After an hour you can see exactly how much wall you built. No room left for the mental chewing.

The line George Mack used in his post, "depression hates a moving target," is good poetry. The science behind it is sharper. Depression hates a brain that has somewhere else to be.

[Contraction Trader @iramyram]

Data Center Stocks Having Their Own Decadal Run In This Market.

[TechieTrader @rk_onkar]

How US market is different than india?
1. Directional cause of liquidity , right stock and you make crazy money
https://t.co/7qSkwWrHn0 longed Pre and post market hours , good for SIPS
3. Hell lot of opportunities
4. No circuit limits and BDSM list
5. methods of EG work as is

[Jeff Sun, CFTe @jfsrev]

@Qullamaggie was the reason I started diving deep into the importance of ADR%, volume run rate (his vol buzz) and LoD <ATR entries to sharpen my performance. He wouldn’t have repeated the same concepts across every streams for 7 years without reason.

I wasn’t as focused on copying the exact setups (many tradable long based setups have the same context as @markminervini @DanZanger @dryan310 concept, but i was more interested in understanding the thought process behind his volatility based stock selection and entry criteria.

Stock selection alone can skew win rate statistics and it’s your consistency in decision making across 10,000 trades that truly reflects performance and edge — and also to be paired with the right situational awareness of course.

I am still trying to improve, I feel I am so way behind in terms of perfecting some volume based concept still

[Suresh K @SureshKBN]

used AI to generate..cross check again ..but quite useful

[Roshan Kumar @RoshanStocks]

Just sharing my prompt, This is my General prompt , You can copy and ask Any AI to alter this prompt for any specific sector/industry/company and ask about about the company also

2 Half prompt - 1st is for people who know abt the company and wants to update and 2nd is for who dont know anything about the company

I would like you view also to improve the prompts

if budget is not an issue, always go with Claude - Give the best answer, Chatgpt also work good

────────────────────────────────────────

General Prompt

Company name: [Company Name]

Sector: [Sector / Industry]

You are a equity analyst. Produce a structured investor-grade analyst report on this company in EXACTLY TWO HALVES as described below. Auto-adjust every section to the company's actual business model, sector dynamics, and available disclosures. Do not produce a generic answer for any section. Every claim must be specific, quantified where possible, and peer-linked.

────────────────────────────────────────

HALF 1 — THE INFORMED INVESTOR BRIEF

────────────────────────────────────────

H1.0 — COMPANY HISTORY (max 5 bullets)

- Founded [year] — original business model in one line
- Key structural pivot(s): product / geography / technology / ownership
- What is fundamentally different today vs 5 years ago?
- One-line on promoter / key ownership change if it altered business direction

Rule: Only include changes that materially altered business economics. No storytelling.

H1.1 — WHAT DOES THIS COMPANY DO (Kid-Friendly, max 10 bullets)

- Explain the business in plain language — no jargon, no abbreviations
- Who are its customers (in simple words)?
- How does it make money?
- Name its 2–3 main business segments in plain words
- One line on its scale / relevance

Rule: A smart 14-year-old must understand after reading this.

H1.2 — LAST QUARTER / LATEST RESULTS SNAPSHOT

- Revenue, EBITDA, PAT: absolute number + YoY % + QoQ % (one line each)
- What surprised vs market expectations? (positive and negative)
- Which specific segment drove the quarterly delta
- 1–2 most important things from management commentary
- Balance sheet / cash flow flag if material
- One-line verdict: did the investment thesis hold or get dented?

Rule: Only mention what changes the investment view.

H1.3 — NEXT 1–2 QUARTERS — WHAT TO EXPECT

- Revenue trajectory: flat / accelerating / decelerating — and specific reason
- Margin trajectory: expansion or compression — with specific driver named
- One key event to watch (capacity commissioning / order conversion / regulatory trigger)
- One risk that could disappoint next quarter
- Where your view diverges from consensus (if it does), and why

Rule: Frame as specific triggers only.

────────────────────────────────────────

HALF 2 — FULL COMPANY DEEP DIVE

────────────────────────────────────────

2.1 — BUSINESS SEGMENTS & ECONOMICS

- List each segment: what it makes/does, who it sells to
- For each segment: EBITDA margin range OR per-unit economics (₹/ton / ₹/unit / %)
- Cyclicality: project-based / recurring / spot-priced per segment
- Certifications / regulatory approvals that create entry barriers per segment
- Where is this company stronger or weaker than peers — per segment

2.1 — BUSINESS SEGMENTS & ECONOMICS

For each segment list the following in order:

A. WHAT IT DOES & WHO IT SELLS TO

- Product / service description in one line
- Named customers, grouped by segment (not a flat list)
- After the customer list: one line on what having these customers signals
(approval depth / switching cost / margin quality / revenue visibility)

Example format:

Aerospace — Airbus, Boeing, Dassault, HAL, Spirit AeroSystems
→ Signals: AS9100 + NADCAP certified, program-linked revenue, avg. tenure 5+ yrs

Hydraulics — Cummins, JCB, John Deere, Mahindra, Eicher
→ Signals: IATF 16949 certified, annual contract + spot, higher volume / lower margin

B. CERTIFICATIONS & APPROVALS (only barriers, not vanity badges)

For each certification: [Name] — [one line: who you cannot sell to without it]

Examples of format:

- AS9100 Rev D — cannot supply Boeing, Airbus, Lockheed Martin, HAL without this
- NADCAP (Heat Treat / NDT) — process-level approval for flight-critical parts; ~30 Indian holders
- IATF 16949 — mandatory for Tier 1 supply to global auto OEMs
- USFDA facility approval — each plant approved separately; 2–4 yr cycle; unlocks US pharma pricing
- SQAE / DRDO vendor registration — mandatory for Indian defence supply; 2–5 yr approval cycle
- R2 / e-Stewards (recycling) — required by ESG-conscious global buyers of recycled content

Rule: Skip ISO 9001 unless a peer lacks it. Only list certifications that restrict competition.

C. IP, TECHNOLOGY & PROPRIETARY KNOW-HOW

- Patent count + jurisdiction (India / US / EU) — compare vs peers
- Proprietary process or formulation (if any) — one line on what it enables
- Licensed technology source + expiry risk (if licensed from a third party)
- Co-development / JDA with customer — signals technical credibility + future program lock-in
- Design capability: does company design the part or manufacture to customer drawing?
(Design capability = pricing power + stickiness vs job-shop = commoditised)
- R&D spend % of revenue — compare vs peers and sector norm

D. AWARDS & VENDOR STATUS (only commercially meaningful ones)

- Preferred / Strategic Vendor designation from named OEM — what it means for order flow
- Sole-source designation (if any) — the highest form of customer lock-in
- Approved Vendor List (AVL) inclusions — prerequisite to quote; not trivial to achieve

Skip: CSR awards, generic industry rankings, export certificates unless tied to revenue proof

E. CAPEX QUALITY & ASSET PROFILE

- Key equipment OEM / origin (German / Japanese / domestic) — signals capability ceiling
- Automation / robotics level vs peers — impact on per-unit cost and quality consistency
- Cleanroom / controlled environment (if applicable) — hard-to-replicate barrier
- Tooling ownership vs leased — owned tooling = customer switching cost

F. SEGMENT ECONOMICS

- EBITDA margin range OR per-unit economics (₹/ton / ₹/unit / %) — quantified
- Revenue cyclicality: project-based / recurring / spot-priced
- Where this company is stronger or weaker vs peers — per segment, not overall

2.2 — REVENUE MIX (MANDATORY — MUST QUANTIFY)

- Segment-wise revenue split in %
- Geography split: India domestic / exports / overseas subsidiaries in %
- Top customer concentration (single client %, top-5 % if disclosed)
- How has the mix shifted over 3 years? What drove it?
- Is current mix better-quality or worse vs peers — and why?
- What mix shift is underway and what it implies for blended margins

Rule: Never say "diversified mix." Quantify it. Example: "33% of volumes at ₹28,000/ton EBITDA via overseas ops; 67% domestic at ₹18,000–19,000/ton."

2.3 — PROFITABILITY MIX

- EBITDA margin or per-unit economics per segment — quantified
- Which segment cross-subsidises which
- Blended margin today and directional impact of mix shift
- Peer margin level: name specific peers + specific reason why this company is higher or lower
- One structural reason why the margin difference is durable or at risk

2.4 — OPERATIONS & CAPACITY (skip if not manufacturing / asset-heavy)

- Each major plant: location + what it produces + installed capacity
- Current utilization % per plant or blended
- Which plant drives margins vs which drives volume
- Capex announced: location, quantum, commissioning quarter
- Post-expansion revenue potential at full utilization
- Capacity profile vs peers: who has more, better-located, or flexible capacity

2.5 — COST STRUCTURE

- Top 3 cost heads as % of revenue — quantified
- Raw material sourcing: spot vs contracted vs captive — and margin stability implication
- Fixed vs variable split — margin impact in a 10–15% volume downcycle
- Structural cost advantage vs peers: name it, quantify where possible
- Structural cost disadvantage vs peers: name it, quantify where possible

2.6 — BUSINESS DRIVERS (SPECIFIC TO THIS COMPANY — NOT GENERIC)

- Primary revenue driver: order book / spot volumes / capacity ramp / pricing
- Order book: size, timeline, revenue recognition pace (if applicable)
- Cyclical / structural / program-linked — with 3-year evidence
- Pricing power: pass-through of cost changes — fully / partially / with lag
- Revenue visibility vs peers: quarters locked in

2.7 — GROWTH TRIGGERS (2–3 YEAR VIEW)

- Each trigger: what it is + expected revenue/volume impact in ₹ or %
- Capacity expansion: commissioning quarter, incremental revenue at full utilization
- New segment / geography: market size, addressable share, timeline
- Industry tailwind: market size (₹ Cr / $ Bn, CAGR), company's current and target share
- Order pipeline / government tender / L1 wins (if applicable)
- Is this company better or worse positioned vs peers to capture these — and why

2.8 — RISKS (SPECIFIC TO THIS COMPANY — NOT GENERIC)

- Execution risk: historical slippages, pattern
- Customer concentration: top client %, switching dynamics
- Working capital: D/E, receivable days, cash conversion vs peers
- Margin collapse scenario: which cost or mix change hits EBITDA fastest
- Regulatory / policy / environmental risk: specific rule or body, not generic
- Name one peer that can outcompete on a specific dimension — explain how

Rule: No lazy risks. Name the competitor and the dimension.

────────────────────────────────────────

2.9 — PEER COMPARISON

────────────────────────────────────────

List ALL relevant peers across three tiers. For each peer, give:

— Company name + exchange:ticker
— ONE specific dimension where it is Superior / Inferior / Comparable to [Company Name]
— Quantify: use per-unit economics, margin bps, D/E ratio, debtor days, or capacity numbers
— Do NOT say "higher margins" — say why: mechanism, mix, geography, integration, feedstock

TIER 1 — CLOSEST INDIAN LISTED PEERS

(Same product, same end-market, direct segment overlap)

List all relevant companies. For each:

[Company (TICKER)] — Superior/Inferior/Comparable — [one specific quantified dimension of difference and the structural reason behind it]

TIER 2 — BROADER INDIAN LISTED PEERS

(Same sector or adjacent — partial overlap in product, customer, or value chain)

List all relevant companies. For each:

[Company (TICKER)] — Superior/Inferior/Comparable — [one specific quantified dimension of difference and the structural reason behind it]

TIER 3 — INTERNATIONAL / GLOBAL PEERS

(Global players in same or adjacent space — for technology, scale, and margin benchmarking)

List all major global players. For each:

[Company (EXCHANGE:TICKER)] — Superior/Inferior/Comparable — [scale, integration, or margin difference with structural reason]

MANDATORY STANDARD: Do not say "higher margins." Say: "EBITDA/ton is ₹X,000 for [company] vs ₹Y,000 for [peer] because [specific structural reason]." Apply this to every metric: margins, working capital, revenue mix, balance sheet.

────────────────────────────────────────

2.10 — WHAT TO TRACK (5–7 KPIs ONLY)

────────────────────────────────────────

- Only metrics that change investment view if they move
- Tie each KPI to a strength or risk identified above
- Include: volume / realization / mix indicator
- Include: capacity utilization trend
- Include: order book trend (if applicable)
- Include: 1 balance sheet metric (net debt/EBITDA or working capital days)
- Include: 1 industry cycle indicator (commodity price / policy event / demand index)
- State a threshold for each: e.g., "watch if EBITDA/ton falls below ₹X — signals mix deterioration"

────────────────────────────────────────

END WITH:

👉 Key Insight: One line on what STRUCTURALLY drives this company's economics above or below peers.

────────────────────────────────────────

FORMAT RULES:

- Bullet points throughout — no paragraphs
- Bold only section headers
- Include ₹ / $ / % / units — no vague qualitative claims
- Strengths and weaknesses embedded inside each section (not separately)
- Skip inapplicable sections silently
- No repeated information across sections
- Half 1: max 6 bullets per section — short and crisp
- Half 2: detailed, specific, company-unique — not generic template text

[Goshawk Trades @GoshawkTrades]

a lot of replies to this are "how do you compete against that?"

you don't. that's the point.

if you're getting into algo trading, you are not going to beat Jane Street at market making. you are not going to out-speed them on order book inefficiencies. you are not going to win at anything that requires sub-millisecond execution.

that is not how you win.

here's how you actually find something you can win in:

1. trade on higher timeframes where speed doesn't matter. trend following, momentum, mean reversion on daily or weekly bars, none of these require nanosecond execution.

2. go where the big funds can't. less liquid markets, newer asset classes, niche sub markets. the capital they manage is too large for those markets to matter to them, but they can matter to you.

3. harvest risk premiums. that doesn't get arbitraged away very fast and can persists because the underlying risk is real.

the biggest mistake I see newer algo traders make is spending months building something that "tries" to compete directly with firms like this. it's a fun project, but it's not going to work.

know which game you're playing. and more importantly, know which game you're not.