Saturday, June 21, 2025

Stock Tips (21-Jun-2025)


Lessons in Investing

Recommendations borrowed from ICICI Direct

Short Term

Medium Term

Stock CMP Recommendation
Price & Date		 Target-1 Stop Loss Potential Upside/
Down Side
 Remark Action
AARTI INDUSTRIES LTD
- Quant Derivatives Pick - 3 month - Buy		 441.3 477.00 11-Jun-2025 560.00 439.00 17.40% Stop Loss Hit
HINDUSTAN AERONAUTICS LIMITED
- Gladiator Stocks - 3 month - Buy		 4973.1 5,110.00 10-Jun-2025 5,672.00 4,718.00 11.00%
ABB INDIA LIMITED
- Gladiator Stocks - 3 month - Buy		 5968.5 6,130.00 09-Jun-2025 6,860.00 5,648.00 11.91%
BANK OF MAHARASHTRA
- Gladiator Stocks - 3 month - Buy		 53.87 56.50 09-Jun-2025 65.00 51.00 15.04%
PHOENIX MILLS LTD
- Gladiator Stocks - 3 month - Buy		 1616.1 1,625.00 09-Jun-2025 1,842.00 1,488.00 13.35%
GODREJ PROPERTIES LIMITED
- Gladiator Stocks - 3 month - Buy		 2432 2,430.00 06-Jun-2025 2,748.00 2,218.00 13.09%
ALLIED BLENDERS AND DISTIL LTD
- Gladiator Stocks - 3 month - Buy		 422.65 415.00 05-Jun-2025 478.00 378.00 15.18% Book 50% profit at 450 and trail stoploss for remaining position to 415
AXIS BANK LIMITED
- Margin Trading Funding (MTF) - 3 Months - Buy		 1220.7 1,200.00 23-May-2025 1,280.00 0.00 6.67% Book 50% profit at 1234.4 and trail stoploss for remaining position to 1185
RELIANCE INDUSTRIES
- Margin Trading Funding (MTF) - 3 Months - Buy		 1466.2 1,420.00 23-May-2025 1,530.00 0.00 7.75% Book 50% profit at 1465 and trail stoploss to 1408 for remaining positions (Return 4%)
TATA POWER CO LTD
- Margin Trading Funding (MTF) - 3 Months - Buy		 390.1 398.00 23-May-2025 445.00 0.00 11.81%
TATA STEEL LIMITED
- Margin Trading Funding (MTF) - 3 Months - Buy		 151.97 163.00 23-May-2025 178.00 0.00 9.20%
BHARAT ELECTRONICS LTD
- Gladiator Stocks - 3 month - Buy		 408.25 377.00 21-May-2025 422.00 344.00 11.94% Book 50% profit at 396 and trail stoploss for remaining position to 374
TATA MOTORS LIMITED
- Quant Derivatives Pick - 3 month - Buy		 676.2 732.00 16-May-2025 830.00 662.00 13.39%
MPHASIS LIMITED
- Quant Derivatives Pick - 3 month - Buy		 2696.1 2,508.00 13-May-2025 2,820.00 2,322.00 12.44% Book 50% profits at 2675 and trail stop loss to 2525 for the remaining positions. (Return= 6%)
LARSEN AND TOUBRO LIMITED
- Gladiator Stocks - 3 month - Buy		 3662 3,530.00 12-May-2025 3,928.00 3,264.00 11.27%
TITAN COMPANY LIMITED
- Gladiator Stocks - 3 month - Buy		 3519 3,562.00 12-May-2025 3,978.00 3,280.00 11.68%
SUN PHARMACEUTICAL INDUSTRIES
- Gladiator Stocks - 3 month - Buy		 1665.1 1,833.00 28-Apr-2025 2,040.00 1,687.00 11.29% Hold on long position with a revised stoploss of 1636
UPL LIMITED
- Quant Derivatives Pick - 3 month - Buy		 633.5 668.00 23-Apr-2025 756.00 617.00 13.17%
STATE BANK OF INDIA
- Gladiator Stocks - 3 month - Buy		 796.15 852.00 03-Dec-2024 950.00 784.00 11.50%


Long Term

Stock CMP Recommendation
Price & Date		 Target-1 Stop Loss Potential Upside/
Down Side
 Remark Action
KEC INTERNATIONAL LTD (FORMER
- Shubh Nivesh - 12 month - Buy		 897.4 878.00 16-Jun-2025 1,050.00 0.00 19.59%
ADITYA BIRLA REAL ESTATE LTD
- Shubh Nivesh - 12 month - Buy		 2424.9 2,359.00 09-Jun-2025 2,850.00 0.00 20.81%
ADANI PORT AND SPECIAL ECONO
- Conviction Ideas - 12 month - Buy		 1349.3 1,433.00 04-Jun-2025 1,670.00 0.00 16.54%
INDIAN BANK
- Shubh Nivesh - 12 month - Buy		 615.65 620.00 02-Jun-2025 740.00 0.00 19.35%
KAJARIA CERAMICS LTD
- Shubh Nivesh - 12 month - Buy		 1022.4 994.00 26-May-2025 1,160.00 0.00 16.70%
DIXON TECHNOLOGIES INDIA LTD
- Conviction Ideas - 12 month - Buy		 14047 16,073.00 13-May-2025 20,000.00 0.00 24.43%
VEDANTA LIMITED
- Conviction Ideas - 12 month - Buy		 447.1 435.00 13-May-2025 600.00 0.00 37.93%
HYUNDAI MOTOR INDIA LIMITED
- Conviction Ideas - 12 month - Buy		 2006.2 1,630.00 15-Apr-2025 2,070.00 0.00 26.99%
AADHAR HOUSING FINANCE LIMITED
- Conviction Ideas - 12 month - Buy		 437.5 459.00 11-Apr-2025 550.00 0.00 19.83%
DALMIA BHARAT LIMITED
- Conviction Ideas - 12 month - Buy		 2040.2 1,812.00 11-Apr-2025 2,160.00 0.00 19.21%
CHALET HOTELS LIMITED
- Conviction Ideas - 12 month - Buy		 897.55 800.00 04-Apr-2025 1,060.00 0.00 32.50%
DLF LIMITED
- Conviction Ideas - 12 month - Buy		 854.25 762.00 06-Feb-2025 1,000.00 0.00 31.23%
GLAND PHARMA LIMITED
- Conviction Ideas - 12 month - Buy		 1723.4 1,515.00 31-Jan-2025 2,005.00 0.00 32.34%
INDIAN HOTELS CO LTD
- Shubh Nivesh - 12 month - Buy		 765.65 782.00 27-Jan-2025 984.00 0.00 25.83%
JINDAL STEEL & POWER LIMITED
- Shubh Nivesh - 12 month - Buy		 899.05 920.00 13-Jan-2025 1,220.00 0.00 32.61%
JINDAL STEEL & POWER LIMITED
- Conviction Ideas - 12 month - Buy		 899.05 940.00 08-Jan-2025 1,220.00 0.00 29.79%
JUST DIAL LIMITED
- Shubh Nivesh - 12 month - Buy		 877.75 1,064.00 06-Jan-2025 1,360.00 0.00 27.82%
LATENT VIEW ANALYTICS LIMITED
- Conviction Ideas - 12 month - Buy		 402.15 483.00 06-Jan-2025 610.00 0.00 26.29%
MAX ESTATES LIMITED
- Conviction Ideas - 12 month - Buy		 500.95 591.00 06-Jan-2025 741.00 0.00 25.38%
ADITYA BIRLA SUN LIFE AMC LTD
- Market Strategy - 12 month - Buy		 755.95 817.00 30-Dec-2024 985.00 0.00 20.56%
KNR CONSTRUCTIONS LIMITED
- Market Strategy - 12 month - Buy		 211.32 315.00 30-Dec-2024 390.00 0.00 23.81%
LARSEN AND TOUBRO LIMITED
- Market Strategy - 12 month - Buy		 3662 3,608.00 30-Dec-2024 4,262.00 0.00 18.13%
MAHINDRA & MAHINDRA LIMITED
- Market Strategy - 12 month - Buy		 3184.4 3,049.00 30-Dec-2024 3,600.00 0.00 18.07%
PIRAMAL PHARMA LIMITED
- Market Strategy - 12 month - Buy		 195.1 255.00 30-Dec-2024 320.00 0.00 25.49%
TECHNO ELECTRIC AND ENGINEERIN
- Market Strategy - 12 month - Buy		 1480.7 1,560.00 30-Dec-2024 1,920.00 0.00 23.08%
THE RAMCO CEMENTS LIMITED
- Market Strategy - 12 month - Buy		 1012.1 966.00 30-Dec-2024 1,180.00 0.00 22.15%
THE RAMCO CEMENTS LIMITED
- Shubh Nivesh - 12 month - Buy		 1012.1 966.00 30-Dec-2024 1,180.00 0.00 22.15%
ASHOK LEYLAND LTD
- Yearly Derivatives - 12 month - Buy		 235.15 220.00 23-Dec-2024 295.00 179.00 34.09% Book 50% profits at 238 and trail stop loss to 215 for the remaining positions. (Return= 11%)
JSW STEEL LIMITED
- Shubh Nivesh - 12 month - Buy		 1005.55 920.00 23-Dec-2024 1,130.00 0.00 22.83%
VEDANTA LIMITED
- Yearly Derivatives - 12 month - Buy		 447.1 485.00 23-Dec-2024 610.00 410.00 25.77%
ZYDUS LIFESCIENCES LIMITED
- Yearly Derivatives - 12 month - Buy		 957.1 990.00 23-Dec-2024 1,320.00 809.00 33.33%
BEML LIMITED
- Yearly Technical Picks - 12 month - Buy		 4639.5 4,250.00 18-Dec-2024 5,390.00 0.00 26.82%
CESC LIMITED
- Yearly Technical Picks - 12 month - Buy		 163.39 180.00 18-Dec-2024 235.00 0.00 30.56%
INDIAN BANK
- Yearly Technical Picks - 12 month - Buy		 615.65 555.00 18-Dec-2024 705.00 0.00 27.03% Book 50% profit at 629 and hold remaining long positions with stop loss of Rs 561
JK LAKSHMI CEMENT LIMITED
- Yearly Technical Picks - 12 month - Buy		 818 820.00 18-Dec-2024 994.00 0.00 21.22%
STEEL AUTHORITY OF INDIA LTD
- Yearly Technical Picks - 12 month - Buy		 127.48 117.00 18-Dec-2024 153.00 0.00 30.77% Book 50% profit at 133.20 and hold remaining long positions with stop loss of 120
TIMKEN INDIA LIMITED
- Yearly Technical Picks - 12 month - Buy		 3279.2 3,160.00 17-Dec-2024 3,950.00 0.00 25.00%
FEDERAL BANK LTD
- Shubh Nivesh - 12 month - Buy		 207.51 213.00 09-Dec-2024 260.00 0.00 22.07%
SAREGAMA INDIA LIMITED
- Shubh Nivesh - 12 month - Buy		 499.7 507.00 02-Dec-2024 610.00 0.00 20.32%
HPL ELECTRIC & POWER LIMITED
- Shubh Nivesh - 12 month - Buy		 531.55 484.00 25-Nov-2024 660.00 0.00 36.36%
BANK OF BARODA
- Shubh Nivesh - 12 month - Buy		 234.15 242.00 18-Nov-2024 300.00 0.00 23.97%
ENGINEERS INDIA LTD
- Shubh Nivesh - 12 month - Buy		 221.17 188.00 11-Nov-2024 240.00 0.00 27.66%
NIPPON LIFE IND ASSET MANAGEME
- Shubh Nivesh - 12 month - Buy		 759.45 711.00 04-Nov-2024 850.00 0.00 19.55%
HDFC ASSET MANAGEMENT CO LTD
- Top Picks - 12 month - Buy		 4958.6 4,580.00 25-Oct-2024 5,500.00 0.00 20.09%
NATCO PHARMA LIMITED
- Top Picks - 12 month - Buy		 875.1 1,390.00 25-Oct-2024 1,680.00 0.00 20.86% Target price was revised downwards to Rs 1305 post Q3FY25 numbers, due to significantly lower than expected traction from one cancer drug Revlimid in the US besides unforeseen pricing pressure and subsequent downgrade in our earnings estimates
NCC LIMITED
- Top Picks - 12 month - Buy		 221.3 300.00 25-Oct-2024 400.00 0.00 33.33%
PCBL CHEMICAL LIMITED
- Top Picks - 12 month - Buy		 390.95 470.00 25-Oct-2024 600.00 0.00 27.66%
SANSERA ENGINEERING LIMITED
- Top Picks - 12 month - Buy		 1327.1 1,590.00 25-Oct-2024 2,000.00 0.00 25.79%
TATA POWER CO LTD
- Top Picks - 12 month - Buy		 390.1 450.00 25-Oct-2024 530.00 0.00 17.78%
TECH MAHINDRA LIMITED
- Top Picks - 12 month - Buy		 1696.1 1,750.00 25-Oct-2024 2,000.00 0.00 14.29%
ACTION CONSTRUCTION EQUIPMENTS
- Shubh Nivesh - 12 month - Buy		 1177.8 1,390.00 21-Oct-2024 1,700.00 0.00 22.30%
JK LAKSHMI CEMENT LIMITED
- Shubh Nivesh - 12 month - Buy		 818 782.00 07-Oct-2024 960.00 0.00 22.76%
AEROFLEX INDUSTRIES LIMITED
- Conviction Ideas - 12 month - Buy		 204.47 178.00 30-Sep-2024 230.00 0.00 29.21%
L&T FINANCE LIMITED
- Shubh Nivesh - 12 month - Buy		 190.05 187.00 30-Sep-2024 225.00 0.00 20.32%
H G INFRA ENGINEERING LTD
- Shubh Nivesh - 12 month - Buy		 1003.9 1,562.00 16-Sep-2024 1,885.00 0.00 20.68%
KALPATARU PROJECTS INTL. LTD
- Shubh Nivesh - 12 month - Buy		 1160.2 1,342.00 02-Sep-2024 1,630.00 0.00 21.46%
STAR HEALTH ALLIED INS CO LTD
- Shubh Nivesh - 12 month - Buy		 425.75 602.00 26-Aug-2024 730.00 0.00 21.26%
SONATA SOFTWARE LIMITED
- Shubh Nivesh - 12 month - Buy		 397.9 616.00 19-Aug-2024 770.00 0.00 25.00%
NTPC LIMITED
- Shubh Nivesh - 12 month - Buy		 335.2 420.00 05-Aug-2024 500.00 0.00 19.05%
JAMNA AUTO INDUSTRIES LIMITED
- Shubh Nivesh - 12 month - Buy		 89.29 136.00 29-Jul-2024 170.00 0.00 25.00%
INDIAN BANK
- Shubh Nivesh - 12 month - Buy		 615.65 559.00 15-Jul-2024 700.00 0.00 25.22%
MISHRA DHATU NIGAM LIMITED
- Shubh Nivesh - 12 month - Buy		 443.3 494.00 08-Jul-2024 600.00 0.00 21.46%
ELGI EQUIPMENTS LTD
- Shubh Nivesh - 12 month - Buy		 510.25 685.00 18-Jun-2024 835.00 0.00 21.90%
BIRLA CORPORATION LTD
- Shubh Nivesh - 12 month - Buy		 1266 1,476.00 10-Jun-2024 1,870.00 0.00 26.69%
NRB BEARINGS LTD
- Shubh Nivesh - 12 month - Buy		 290.2 322.00 21-May-2024 400.00 0.00 24.22%
Tags: Investment,Finance,
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Thursday, June 19, 2025

Remembering Garima Sethi (Jun 2025)


Other Journaling Days

Fictional illustration of a real person using ChatGPT 
This was in 2010.
I first came across Garima Sethi mam when I joined my classmates from 2009 batch in the middle of third semester.

I had got an year back in first year but that rule was lifted for the students from current academic session. “Year Back” rule was a brutal decision by the GGSIPU against the students not serious in studies or not securing a minimum amount of score or percentage in the exams.

In the first year, I mostly wasted my time in fooling myself into thinking that if I would sit for IITJEE for a second time, maybe I would get better results. It turned out I was having a disturbed sleep and waking hours from more than normal amount of caffeine intake.

Well, I was sleeping in the 6 hours long exam due to not drinking tea in the break after the first half of the exam consisting of two sessions.

I may have digressed but what I wanted to share was that I was already in a bad shape even before I was going to meet Garima Sethi. Garima Sethi, who was going to make my life hell.

Surprisingly, she had one of the few important subjects during that time (my time of 2009-2013, before Data Analytics, Data Science, Machine Learning, AI or Gen AI were there).

In the third semester, she was teaching Data Structures and Algorithms. A more detailed analysis and design of algorithms came 4rth semester as taught by Prashant Sharma sir, the subject was called ADA (abbreviation of Algorithms – Design and Analysis).

The grudge I held against her… well, I held multiple grudges but this seems to be one of the first and foremost one. 

In the time that I was absent from the third semester and attending classes in new Humanities building with the fresh entrants in new session of first semester, Garima Sethi had already taught one of the most important lessons of DSA.

“Psuedo code can be written in plain English. It doesn’t have to cryptic, it don’t have to be like a programming language itself like how any psuedo-code was written in that TMH book (Schaum's Outline of Data Structures).”

I missed this one detail and suffered with the back in the subject.
It wasn’t just this subject though. I don’t recall what other subjects I got a back log for in third semester but DSA was an important subject.
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Interview Questions on "Arrays" - Ch 2 - Fluent Python

All Posts on Python

Interview Questions from "Fluent Python" Chapter 2: Sequences

Easy Questions

  1. What are the two main categories of sequences based on mutability?

  2. How do container sequences differ from flat sequences?

  3. What is the key advantage of list comprehensions over map/filter?

  4. How do you prevent list comprehensions from leaking variables (Python 2 vs. Python 3)?

  5. What is the purpose of collections.namedtuple?

  6. How does tuple unpacking work in Python?

  7. What does the * operator do in tuple unpacking (e.g., a, *rest = [1, 2, 3])?

  8. Why do Python slices exclude the last item (e.g., my_list[0:3])?

  9. How do you reverse a sequence using slicing?

  10. What is the difference between list.sort() and sorted()?

Medium Questions

  1. Explain how generator expressions save memory compared to list comprehensions.

  2. How would you use a list comprehension to generate a Cartesian product?

  3. When should you use bisect instead of the in operator for membership tests?

  4. How does bisect.insort maintain a sorted sequence efficiently?

  5. Why might array.array be preferable to list for numerical data?

  6. What is the purpose of memoryview in handling large datasets?

  7. How does deque.rotate() work, and when would you use it?

  8. What happens when you assign to a slice (e.g., my_list[2:5] = [20, 30])?

  9. Why does my_list = [[]] * 3 create a list with shared references?

  10. How does the key parameter in sorted() enable case-insensitive sorting?

Complex Questions

  1. Explain the behavior of a += b for mutable vs. immutable sequences.

  2. Why does t[2] += [50, 60] raise a TypeError but still modify a tuple’s mutable element?

  3. How does NumPy’s ndarray improve performance for numerical operations?

  4. Discuss the performance trade-offs of using deque vs. list for FIFO/LIFO operations.

  5. How can memoryview.cast() manipulate binary data without copying bytes?

  6. When would you use array.tofile() instead of pickle for saving numerical data?

  7. Explain how the key parameter in sorting functions leverages stability (e.g., Timsort).

  8. How does bisect support efficient table lookups (e.g., converting scores to grades)?

  9. Why is deque thread-safe for append/pop operations?

  10. Compare the performance of array.fromfile() vs. reading floats from a text file.

These questions cover core sequence operations, performance optimizations, and practical applications from the chapter, suitable for evaluating a candidate's depth of understanding.

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Wednesday, June 18, 2025

The Unspoken Truths of Life, Death, and Everything In Between (2025-Jun-18)


Other Journaling Days 
“What really matters when you die?”
“What really matters when you are dying?”

Once you are dead, I don't think anything matters thereafter.
But once you are dying… Is it wrong to ask for a little bit of comfort, a little bit of support of “a family”? Or are we supposed to just be aware of our death and accept it the way it is?

“What if you are in sickness? What if you are sick?”
Are we just supposed to pass away quietly still? Without bringing any discomfort to anyone, anybody.

One thing I am definitely not supposed to worry about is the expectations of other people. If they are “empty handed”, they would like a dollar. If they have a dollar, they would want 2 dollars or 10 dollars.

You can't even die in peace. Just if you like more context, I am talking about my mother.

I don't know what I am talking about. I don't know what to write about. 

This day of low health (but really good weather with cloudy sky and a day out at the temple) made me think about my death in my meditation. 

Speaking of death: what are my assets and what are my liabilities?

At the end of the day, a conversation about death circles back to money and finance.
How much do you have?
How much do you owe?

I owe my SBI bank some 41 lakh rupees. But that is a home loan, considered a “good loan” - one that is backed by an asset.

Surprisingly, nothing else :D 
There was a car loan also but I repaid that one. :D

My assets are at a low. At about 3.5 lakhs. I mean I wouldn't know what I would do in an emergency. Times are tough.

Dikhya just pinged with a “?”
I sent her a quick text “call?” Followed by :
“I was not keeping well.
Could not raise the matter with you.
Apologies for my absence. Pls convey my message to your father also who was trying to reach out.
Not a good day. Feeling low.”

I hope it resolves the issue and any miscommunication or any communication gap.

I think I am going to watch one of Ankur Warikoo's videos on Finance and rest and relax with it.

There is this book by Ankur Warikoo that's titled “Make Epic Money”. I don't know what to make out of the title because sometimes making Epic money would seem like an unreasonable target when all you want to do is just come out of a financial trough.

Thanks!
God bless!
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What is the Python Data Model?

All Questions From This Chapter

The Python Data Model is the framework that defines how Python objects behave and interact with each other. It’s the foundation for all built-in behavior in Python, such as arithmetic operations, attribute access, iteration, string representation, and more.

🧩 Key Idea:

The Python Data Model is made up of special methods (a.k.a. "dunder" methods — methods with double underscores like __len__, __getitem__, __str__, etc.) that let you hook into the language’s syntax and built-in functions.

🔍 Examples of Special Methods and What They Enable:

MethodTriggered byUse Case
__len__len(obj)Make object countable
__getitem__obj[index]Indexing, slicing support
__iter__for item in objMake object iterable
__str__str(obj) or print(obj)Human-readable string representation
__repr__repr(obj)Debug-friendly object display
__call__obj()Make object behave like a function
__add__obj1 + obj2Operator overloading
__bool__if obj:Truthiness of an object

🎯 Why It Matters:

  • Lets you create custom classes that integrate seamlessly with Python’s built-in operations.

  • Powers frameworks like Django, Pandas, NumPy, and more.

  • Enables writing Pythonic, intuitive, and idiomatic code.

📘 Example:

python
class Word:
    def __init__(self, text):
        self.text = text

    def __len__(self):
        return len(self.text)

    def __str__(self):
        return f"Word: {self.text}"

word = Word("Python")
print(len(word))    # → 6
print(str(word))    # → Word: Python

📚 Summary:

The Python Data Model is what allows Python to be flexible, expressive, and powerful. It’s the secret sauce behind how user-defined classes can behave like built-in types.

Want to dive deeper into this? Luciano Ramalho's "Fluent Python" is an excellent book focused on this very concept.

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