r/STOCKMARKETNEWS

Most market forecasters have the same problem.

They post a forecast in the morning. The market closes. They move on.

Nobody measures. Nobody improves.

I decided to change that.

The Problem With "I Was Right"

After years of analyzing Nifty 50 intraday movements, I realized something uncomfortable.

I could look at my forecast at 3:30 PM and say "I got the direction right." But that told me almost nothing useful.

Was I right at 9:15 AM or only after 2:00 PM? Was my model 10 minutes early or 10 minutes late? Did I get the morning session right but miss the afternoon? Was Model A better than Model B today — and by how much?

These questions had no answers. Until I built something to answer them automatically.

What I Built

A real-time Nifty 50 forecast accuracy engine that runs , updates every minute during market hours, and computes 30 different metrics automatically.

It looks like a standard chart. But under the hood it is doing something most trading tools don't do — comparing forecast shape against live market data, minute by minute, all day long.

Here is what it tracks:

Correlation metrics:

• Full day Pearson correlation
• Last 60, 30, 15 and 5 minute rolling windows
• Best matching 30-minute window of the day
• Worst matching 30-minute window of the day

Direction accuracy:

• Overall up/down direction match percentage
• Up move accuracy separately
• Down move accuracy separately
• Longest correct direction streak
• Current streak at any moment

Magnitude accuracy:

• Average error per bar in points
• Percentage of bars within 5, 10 and 20 points
• Maximum error (worst single minute)

Time shift detection:

• Is the forecast running early or late vs actual?
• By how many minutes?
• At what shift does correlation peak?

Session analysis:

• Morning session match (9:15 to 12:00)
• Afternoon session match (12:00 to 15:30)

Trend accuracy:

• Did forecast predict the right day direction?
• Did it catch the peak within 30 minutes?
• Did it catch the trough within 30 minutes?
• How close was the forecast high vs actual high?
• How close was the forecast low vs actual low?
• End of day accuracy

Overall:

• Composite weighted score
• Automatic ranking when running multiple models

The Discovery That Changed Everything

The most surprising metric was time shift.

For weeks my correlation scores looked decent — around 65 to 70 percent. I thought that was reasonable. Then I added time shift detection.

It showed my model was consistently running 10 to 15 minutes ahead of the actual market.

The forecast shape was correct. The timing was off.

Once I knew that, I could account for it. Within two weeks my full day correlation jumped from 68 percent to 81 percent — not because my model got better, but because I finally understood how it was wrong.

You cannot fix what you cannot measure.

Running Multiple Models

The second insight came from comparing models side by side.

I run three different forecast approaches each morning. Before this tool I would look at them visually and pick the one that "felt" most reasonable.

Now I have a comparison table. Every metric. Every model. Automatically ranked.

Some days Model A wins on correlation but Model B wins on direction accuracy. Some days one model nails the morning session while another gets the afternoon right.

The table shows exactly where each model is strong and where it falls apart. That is information you cannot get from looking at lines on a chart.

The chart itself has full interactions — hover tooltips, crosshair, zoom, pan, timeframe switching from 1 minute to 30 minutes, moving averages. What the Hover Shows

When you move your cursor over the chart you see:

• Exact time label
• Live Nifty value at that minute (change from open)
• Each forecast model value at that minute
• Difference between actual and forecast in points

In the analysis table every cell highlights the best performer in green. You can see at a glance which model is winning, which metric each model leads, and what the composite score is right now.

What This Is Not

This is not a trading system. It does not give buy or sell signals.

It is a measurement and improvement tool. Its job is to tell me honestly how accurate my forecast was today — in 30 different ways — so I can understand my model better and improve it over time.

The goal is not to be right every day. The goal is to understand exactly how and when and why I am wrong, so the model gets better over time.

What Is Next

will update and have real time from Monday or whatever possible at earliest

The Bigger Point

Anyone can post a forecast. Very few people measure it rigorously.

If you are serious about market forecasting — intraday or otherwise — you need a measurement system as rigorous as your forecasting system.

Otherwise you are flying blind and calling it analysis.

Build the feedback loop. Measure everything. Improve systematically.

That is how forecasting becomes a skill rather than a guess.

*I publish daily Nifty 50 intraday forecasts along with real-time accuracy tracking. Follow for updates on methodology, results and the ongoing development of this tool.*They post a forecast in the morning. The market closes. They move on.

Nobody measures. Nobody improves.

I decided to change that.

The Problem With "I Was Right"

After years of analyzing Nifty 50 intraday movements, I realized something uncomfortable.

I could look at my forecast at 3:30 PM and say "I got the direction right." But that told me almost nothing useful.

Was I right at 9:15 AM or only after 2:00 PM? Was my model 10 minutes early or 10 minutes late? Did I get the morning session right but miss the afternoon? Was Model A better than Model B today — and by how much?

These questions had no answers. Until I built something to answer them automatically.

What I Built

A real-time Nifty 50 forecast accuracy engine that runs , updates every minute during market hours, and computes 30 different metrics automatically.

It looks like a standard chart. But under the hood it is doing something most trading tools don't do — comparing forecast shape against live market data, minute by minute, all day long.

Here is what it tracks:

Correlation metrics:

• Full day Pearson correlation
• Last 60, 30, 15 and 5 minute rolling windows
• Best matching 30-minute window of the day
• Worst matching 30-minute window of the day

Direction accuracy:

• Overall up/down direction match percentage
• Up move accuracy separately
• Down move accuracy separately
• Longest correct direction streak
• Current streak at any moment

Magnitude accuracy:

• Average error per bar in points
• Percentage of bars within 5, 10 and 20 points
• Maximum error (worst single minute)

Time shift detection:

• Is the forecast running early or late vs actual?
• By how many minutes?
• At what shift does correlation peak?

Session analysis:

• Morning session match (9:15 to 12:00)
• Afternoon session match (12:00 to 15:30)

Trend accuracy:

• Did forecast predict the right day direction?
• Did it catch the peak within 30 minutes?
• Did it catch the trough within 30 minutes?
• How close was the forecast high vs actual high?
• How close was the forecast low vs actual low?
• End of day accuracy

Overall:

• Composite weighted score
• Automatic ranking when running multiple models

The Discovery That Changed Everything

The most surprising metric was time shift.

For weeks my correlation scores looked decent — around 65 to 70 percent. I thought that was reasonable. Then I added time shift detection.

It showed my model was consistently running 10 to 15 minutes ahead of the actual market.

The forecast shape was correct. The timing was off.

Once I knew that, I could account for it. Within two weeks my full day correlation jumped from 68 percent to 81 percent — not because my model got better, but because I finally understood how it was wrong.

You cannot fix what you cannot measure.

Running Multiple Models

The second insight came from comparing models side by side.

I run three different forecast approaches each morning. Before this tool I would look at them visually and pick the one that "felt" most reasonable.

Now I have a comparison table. Every metric. Every model. Automatically ranked.

Some days Model A wins on correlation but Model B wins on direction accuracy. Some days one model nails the morning session while another gets the afternoon right.

The table shows exactly where each model is strong and where it falls apart. That is information you cannot get from looking at lines on a chart.

The chart itself has full interactions — hover tooltips, crosshair, zoom, pan, timeframe switching from 1 minute to 30 minutes, moving averages. What the Hover Shows

When you move your cursor over the chart you see:

• Exact time label
• Live Nifty value at that minute (change from open)
• Each forecast model value at that minute
• Difference between actual and forecast in points

In the analysis table every cell highlights the best performer in green. You can see at a glance which model is winning, which metric each model leads, and what the composite score is right now.

What This Is Not

This is not a trading system. It does not give buy or sell signals.

It is a measurement and improvement tool. Its job is to tell me honestly how accurate my forecast was today — in 30 different ways — so I can understand my model better and improve it over time.

The goal is not to be right every day. The goal is to understand exactly how and when and why I am wrong, so the model gets better over time.

What Is Next

will update and have real time from Monday or whatever possible at earliest

The Bigger Point

Anyone can post a forecast. Very few people measure it rigorously.

If you are serious about market forecasting — intraday or otherwise — you need a measurement system as rigorous as your forecasting system.

Otherwise you are flying blind and calling it analysis.

Build the feedback loop. Measure everything. Improve systematically.

That is how forecasting becomes a skill rather than a guess.

I publish daily Nifty 50 intraday forecasts along with real-time accuracy tracking. Follow for updates on methodology, results and the ongoing development of this tool.

ALL stories eventually END, the pages are turned and the cover gets closed, done over. CRUSH thru all the hype, fluff, etc. from false advertising and marketing. Just like glue holding sesame seeds on a burger bun commercial - its misleading, false, untrue, deceptive. It does NOT pass the smell test, or taste test, or actually "cutting thru the middle" to see what is inside - test. The financing will end, there is no equity, no assets, no worth, no value . Built on fraud, house of cards, shell companies, etc.

NELSON MARK A, Vice Chairman at Chevron, sold 139,600 shares at $187.92 per share, for roughly $26.23M, filed 2026-03-02. For a bearish read, that’s a high-significance insider sale at a fairly specific price level, and it puts a large block of stock on the tape from someone close to the business.

What makes it worth noting is the role and the size: this wasn’t a small director sale, but 139,600 shares from the Vice Chairman. Insiders sell for plenty of personal reasons, but large selling from a senior executive still deserves attention.

The 33-factor read on $$CVX with the calculated levels: $CVX

A decade ago, I was buying stocks based on broker tips and using leverage.

Today, I realize that investing is far more about temperament than intelligence.

I began investing in 2016.

Like many beginners, I relied on my broker's tips. They even encouraged me to use leverage to increase my exposure.

Within months, I was sitting on significant losses.

That was my wake-up call.

I stopped chasing tips and decided to educate myself. After taking a short break, I restarted my journey through mutual funds.

I still remember walking into a mutual fund company's back office, unaware that they didn't accept direct investments from retail investors. The employees smiled at my innocence before introducing me to an agent who helped me get started.

Towards the end of 2018, I made another mistake.

I took a Loan Against Securities (LAS) worth around 25% of my portfolio, intending to use it for home renovations.

Then came 2019.

I came across a seasoned investor on Twitter who had achieved financial independence at a young age. Coincidentally, he lived in my hometown.

We met, connected instantly, and over time, he completely transformed the way I approached investing. That's when I transitioned from mutual funds to building a portfolio of fundamentally strong businesses.

The very first thing he told me was:

"Pay off your LAS."

Thankfully, I listened.

Had I ignored that advice, the COVID crash would likely have forced my lender to liquidate my portfolio near the bottom.

He also shared a lesson that has stayed with me ever since:

Exciting stories create headlines. Boring businesses with strong fundamentals create wealth.

From then on, we focused on buying fundamentally strong businesses at sensible valuations instead of chasing the next big thing at any price.

Did I miss some of the market's biggest winners?

Probably.

Do I regret it?

Not at all.

Over time, I also realized that the process matters more than the outcome.

I can't control what the market does in the short term.

But I can control the quality of businesses I invest in, the price I pay, and my discipline.

If the process is sound, the outcomes usually follow.

March 2020

When my portfolio was down nearly 55%, I invested every spare rupee I had.

My thinking was simple:

«If the world ends because of the pandemic, money won't matter.

If it survives, this is the opportunity of a lifetime.»

Eventually, my patience paid off. Businesses that had once looked too expensive were suddenly available at valuations I never thought I'd see.

I felt like a kid in a candy store—I wanted to buy everything.

One amusing memory from that period:

My wife couldn't recharge her phone and genuinely thought our bank account had been hacked.

It turned out I had invested almost every spare rupee into the market. 😅

The Biggest Lesson

The hardest part of investing isn't buying. It's holding.

Fear and greed can cloud judgment. Holding a stock that's gone up 10x is often far more difficult than holding one that's down 50%.

I've sold only two companies in my entire investing journey, both because their fundamentals deteriorated due to corporate governance issues. Those decisions resulted in losses of around 70–80%.

On the other hand, I've continued holding companies that went through 40–50% price corrections because nothing had changed in the underlying business.

Fundamentals—not price—should determine when you buy and when you sell.

My wife deserves a great deal of credit.

Initially, she couldn't understand why, despite earning way more than our peers, we chose to live a comfortable life rather than a luxurious one.

We still went on domestic and international vacations, celebrated milestones, and enjoyed life along the way.

We simply refused to overpay for things or spend money just to impress others.

No luxury cars.

No flagship phones.

No designer clothes.

Over time, she understood what I was trying to build.

Today, she's even more disciplined with money than I am and often calls me out when I spend unnecessarily.

Fast Forward to 2026

I continued investing most of my earnings consistently.

This is where a decade of learning, discipline, and compounding has brought me—not through brilliance, but by surviving mistakes, staying invested, and trusting the process.

Today, my portfolio is at an all-time high and continues to reach new peaks, even though the Nifty is still around 2,000 points below its own all-time high.

Markets have started rewarding valuation discipline over growth at any price. Many of the businesses I owned were re-rated as valuations normalized and fundamentals once again took center stage.

Looking back, I wasn't successful because I was the smartest investor.

I was successful because I survived my mistakes, found the right mentor, stayed invested, and gave compounding enough time to do the heavy lifting.

My Biggest Learnings

1. Margin of safety and capital protection should always come first.

2. Never take a Loan Against Securities (LAS) on your portfolio. A market crash can force you to sell at the worst possible time.

3. The process is more important than the outcome. Focus on buying good businesses at sensible valuations.

4. Don't hesitate to hire a good financial advisor. We don't perform surgery on ourselves when we need medical help—we hire doctors. Same applies here.

5. Holding great businesses is much harder than buying them. Fear and greed will constantly tempt you to sell. If the fundamentals remain intact, temporary price corrections are just noise.

6. Let fundamentals—not stock prices—drive your investment decisions.

7. Investing is a marathon, not a sprint. Stay invested long enough for compounding to work its magic.

If this post helps even one new investor avoid the mistakes I made, it'll be worth writing.

You don't need to be an investing genius. You just need to survive your early mistakes, keep learning, and stay in the game long enough for compounding to work.

Happy investing! ✌️

P.S.: Please don't ask about my current holdings, allocations, or buy prices. A great business isn't always a great investment at today's valuation. I hope the process shared in this post is more valuable than a list of stock names.

Most people who followed $CYDY remember March 30, 2021. The FDA publicly stated that CytoDyn's claims about leronlimab were "misleading and not supported by the data", no benefit was shown in COVID-19 treatment trials. The stock dropped 25%+ that day.

What happened afterward was a class action lawsuit covering investors who held $CYDY between March 27, 2020 and March 30, 2022.

A $500,000 settlement has been reached and terms are now submitted to the court for approval.

Who qualifies?

Anyone who held $CYDY during the class period and suffered losses from the alleged misrepresentations about leronlimab's effectiveness for HIV and COVID-19.

Can I still apply?

Yes, you can submit your application now and it will be processed once claims filing officially opens after court approval.

If you were damaged by this don't forget to check your eligibility. GL!