r/DayTradingPro

Hey folks, I recently set up a claude MCP connector to the robinhood platform in order to trade. First 2 weeks were straight butter, and claude could not be stopped. Then he had a losing day for first time in his 3rd week last week.

I am giving full transparent updates and not trying to hide any of the progress or trades it makes on TQQQ and SQQQ. You can find all of the previous week posts in this sub as well if you look around.

note: I only got to perform 1 trade day last week with my bot because I was out for vacation during the 4th of july weekend. The 1 trade it made was a losing trade so week 3 goes down as a loss unfortunately.

I will be spinning him up every day again this coming week as I will have more time to keep an eye on things. I still don't fully trust him yet, but he is slowly giving me confidence.

strategy: I trade TQQQ and SQQQ only and make 1 trade per day. its simple and straight to the point. we try to ride the daily momentum one way or other after morning breakouts.

what type of bots are yall building and trying to make work?

Some background first: I've spent 3+ years building and running automated futures strategies on the IBKR API, and honestly, none of this would exist without that scar tissue. Alpaca's options API is a different beast (in some ways easier, in some ways much weirder), but knowing what a live bot does to you at 3:25 PM on a bad day is transferable knowledge.

So — the whole thing is on GitHub now. Not a framework with the good parts removed — the actual entry logic I run every morning, all the parameters, the risk management, and the 22-page strategy manual with every session post-mortem, losing days included.

Code + manual: github.com/milgar7969/alpaca-options-framework
Live results: milgar7969.github.io/spy-0dte-dashboard — updates itself daily after the close, green or red

It's paper trading, last 30 days are green, May was rough, and the dashboard will tell on me either way.

Half the value is honestly the README and the pdf manual, which document every Alpaca options landmine I stepped on: bracket orders rejected, null Greeks on 0DTE, and cancelled buy orders that fill anyway (ask me how I know).

Credit where it's due: this is a human + AI collaboration. I built and run this with Claude (Anthropic's model) as my pair programmer — it wrote a lot of the code, caught bugs in the logs I'd have missed, and talked me out of some bad ideas.

The strategy calls, the market experience, and the stubbornness are mine. I'd rather be upfront about that than have the haters leave negative comments.

Clone it, break it, tell me what I did right and what I got wrong.
p.s. there are a lot of knowledge, from my years of experience I am sharing for free, so please be nice ;-)

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.

I’m a 16 year old unprofitable trader with 14 months of experience. In total I have spent exactly $1973 on evals (I work a job btw if anybody was wondering where the money is from).

Passed 4 evals so far and can never seem to get a payout.

I would love some advice if anyone is willing to share.

May and June were my best-performing months of the year. In May, my portfolio grew by SGD 49,049 (+8.94%). The focus in June wasn't on chasing higher returns, but on maintaining discipline. Looking back at my trading log, what satisfies me most isn't the profit or loss figures, but the fact that I consistently adhered to my established rules.

I realize that two months of strong performance can be just as risky as two months of poor performance. It is easy to become overconfident, leading one to blindly increase position sizes or execute trades that deviate from the trading plan.

For July, I intend to stay the course and make no changes:

Position sizing remains the same.

Risk management methods remain the same.

Trading strategy remains the same.

I will maintain rationality in my decision-making, free from emotional interference.

I am sharing these experiences simply to document my trading journey; it is by no means because I believe I have mastered everything. The market always has its ups and downs, and I am constantly learning every day.

After a month of strong performance, how do you adjust your trading strategy? Do you stick with your existing strategy, or do you reduce risk and recalibrate？

>Colossians 1:16-17 For by Him were all things created, that are in heaven, and that are in earth, visible and invisible, whether they be thrones, or dominions, or principalities, or powers: all things were created by Him, and for Him: And He is before all things, and by Him all things consist.

>Philippians 2:10-11 That at the name of Jesus every knee should bow, of things in heaven, and things in earth, and things under the earth; And that every tongue should confess that Jesus Christ is Lord, to the glory of God the Father.

>Jude 1:24-25 Now unto Him that is able to keep you from falling, and to present you faultless before the presence of His glory with exceeding joy, To the only wise God our Saviour, be glory and majesty, dominion and power, both now and ever. Amen.

Buy 110c before the market closes on Tuesday

Grew $504 to $23k in two days

Exhausted Buyers, huge sell order block, big negative delta close, clusters of 5x and 10x sell side imbalances.

>Matthew 24:6 Ye shall hear of wars and rumours of wars: see that ye be not troubled: for all these things must come to pass, but the end is not yet.

>1 John 5:13 These things have I written unto you that believe on the name of the Son of God; that ye may know that ye have eternal life, and that ye may believe on the name of the Son of God.

>Joshua 24:15 If it seem evil unto you to serve the LORD, choose you this day whom ye will serve: but as for me and my house, we will serve the LORD.

That might sound strange, but I built IMALI so users stay in control.
When you press Start, the platform begins scanning markets based on your selected strategy. It looks for opportunities that meet the strategy’s rules and risk parameters before considering a trade.
When you press Stop, the bot stops opening new positions. You stay in control instead of wondering what the software is doing.
A few other controls I built because I wanted them myself:
• Switch between Paper and Live Trading in seconds.
• Choose your own trading strategy based on your risk tolerance.
• Set your preferred market (Crypto, Stocks, Futures, or DEX where supported).
• View every trade from one dashboard.
• Connect or disconnect your exchange whenever you want.
My goal wasn’t to create a “black box” bot.
It was to build software that helps people understand what their automation is doing while giving them the ability to take over at any time.
If you’re curious, you can try the one-click demo here:
👉 https://imali-defi.com/trade-demo
I’d love your feedback.

Will give you access to a private channel. Let me know if interested. I am being genuine here, you got nothing to lose. Dont waste this opportunity!

As many people are interested in my methods, I have received a large number of comments and private messages. To make it easier to share information, I have set up a free study group. I might miss some comments or messages, so if you are interested, please feel free to send me a direct message, and I will reply as soon as possible.

Hey folks, I am back with fresh trading data after the end of last week. Keeping everyone updated on its progress as I go. I am now on week 2 of my claude algo trading bot and its going great so far. I am becoming convinced slowly that this is a legit strategy, but still skeptical a bit as im only done with 2 weeks so far, and going into week 3 tomorrow.

How it works: I try to just trade TQQQ and SQQQ and get it right each day. if i get it wrong i stop for the day.

day 1: buy TQQQ

Day 2-9: buy SQQQ only and 2 days skipped due to filter rules of 1.5% overnight gap

I set up a custom ruby script that runs my algorithm using candle data and then it writes signals to a file that I have wrapped in a process by claude. It could definitely be improved but claude MCP to robinhood got me up and running quickly. I had the entire thing built and backtested in 1 day after chatting with a buddy at dinner the night before about the strategy to use.

anyways, im definitely still learning, but this is so much fun and a great learning journey!

what type of bot strategies are yall using to scalp profits each day?

I am 48 years old and have spent the last 17 years navigating the ups and downs of the financial markets. I have experienced both spectacular successes and devastating setbacks even being forced to start over from scratch. Ultimately, my success stems not from "all or nothing" trades aimed at overnight riches, but from a robust, repeatable trading system that prioritizes risk management.

The results have exceeded my expectations so far, with my investment portfolio more than doubling in size. Of course, the journey has inevitably included days of losses and losing positions.

The key is that I strictly adhere to a set plan for every trade: defining risk before entering, cutting losses decisively when things go wrong, and maintaining consistent position sizing. My goal isn't a 100% win rate; instead, I focus on keeping losses manageable and driving asset growth through profitable trades.

My plan is simple: accumulate a net worth of approximately $5 million over the next year, then quietly retire and travel the world with my wife.

I run a stock discussion group where I share free daily market insights, covering stock selection logic, risk warnings, trading opportunities, and entry points. I share my strategies and experience at no cost, hoping to help those eager to learn, seeking inspiration, or interested in different perspectives on achieving financial freedom. If you are also pursuing financial freedom, feel free to reach out or share your thoughts I’m always happy to exchange ideas and grow together. Please note that this post does not constitute investment advice; I read and reply to every private message.

Wishing everyone successful trading!