Technically Sorted
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My Algorithmic trading set up has signaled a BUY in Mphasis in the first hour of trade today.

The CMP is 2252

One can keep on radar for short term positional.
Technically Sorted pinned ยซhttps://www.linkedin.com/posts/mohak-pachisia-0a56a71b6_algorithmictrading-quantitativefinance-tradingstrategy-activity-7034482794332364801-fGx5?utm_source=share&utm_medium=member_androidยป
Cast your anonymous vote: If I were to ask your willingness to risk your money on a trading strategy. I show you various returns summary reports. On the basis of the given below parameter of profit expectancy and distribution. Which one would you chose?
anonymous poll

Strategy 1 : Total trades in 2 years = 55 Profiting trades = 40 Losing trades = 15 Avg profit = 1% Avg loss = .7% Net profits = โ€“ 35
๐Ÿ‘๐Ÿ‘๐Ÿ‘๐Ÿ‘๐Ÿ‘๐Ÿ‘๐Ÿ‘ 63%

Strategy 2 : Total trades in 5 years = 72 Profiting trades = 34 Losing trades = 38 Avg profit = 3.6% Avg loss = 0.95% Net profit โ€“ 21
๐Ÿ‘๐Ÿ‘๐Ÿ‘๐Ÿ‘ 38%

๐Ÿ‘ฅ 56 people voted so far.
Sorry the after the word "Net Profit". . nothing has come in the options because of word limit.

So consider the rest of the info
Hint: think and vote!. . .they both are automated.
In case of strategy 1:
Even though we know what the statistical terms mean, like mean and mode. We tend to think of them as different. The first thing that comes to a person mind is average profit % will be what I would see every time there is a profit.

However, 1 profit is 10% . . . that means from the net profit of 44.5% . . . 10% is contributed by only one trade. Without it, the strategy is giving us 34.5% is 2 years and average profit % becomes 0.885%.
So, in case you put money on this for 1 years and that same 10% trade doesnโ€™t come about in that period. Then the returns will be much lower than expected.
In case of strategy 2:
There are a total of 34 profiting trades.
Of which 21 have profits above 2% and 12 above 4%
Meaning to say, higher returns are more consistently distributed. So if I am putting my money for one year, then I am more likely to get the 3.6% average profit.
Varying profits are also showing that it will follow some trend and if the trend is sizeable, it can follow it for bigger returns and square off when the trend was short lived.
FREE webinar, ๐—•๐—จ๐—œ๐—Ÿ๐——๐—œ๐—ก๐—š ๐—”๐—Ÿ๐—š๐—ข๐—ฅ๐—œ๐—ง๐—›๐— ๐—œ๐—– ๐—ง๐—ฅ๐—”๐——๐—œ๐—ก๐—š ๐—ฆ๐—ง๐—ฅ๐—”๐—ง๐—˜๐—š๐—œ๐—˜๐—ฆ ๐—œ๐—ก ๐—ฃ๐—ฌ๐—ง๐—›๐—ข๐—ก
Here is what we will cover :

1. Introduction to useful Python packages and libraries.
2. Data check.
3. Trading logic
4. Coding a trading strategy hands on
5. Industry wide practices.
6. Generating backtest results
7. Forward testing
8. Scrutinising returns parameters
9. Ask me anything!! FAQ's and doubt solving!

We will disucss on various topics in such a manner that even a beginner can easily grasp the concepts, step by step.

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Here is the zoom meeting link given below:
The webinar is free and open for all. Pls enter timely.

Timings : 2:00 pm to 4:00 pm, IST(Indian Standard Time)
Date : 2nd April, 2023 (Sunday)

https://lnkd.in/dwYGqKKQ

Meeting id : 884 9645 2140
passcode : 1234

(You may share and like for better reach)

#algorithmictrading #quantitativefinance #tradingstrategy
Technically Sorted pinned ยซhttps://youtu.be/kCoJgXxrKIkยป
This webinar will be conducted in Hindi :

Webinar ke topics, naye aur Visheshagya Trading ke vidyarthiyon ke liye :

1.) Financial data aur trading/investing models ka background.
2.) Trading ko coding aur automation mein kaise badle.
3.) Ek achhi trading strategy mein kya dekha jaata hai, aur returns analysis.
4.) Strategy backtesting ki โ€˜LIVEโ€™ coding, class mein.

Jo Python language ko nahi jaante hain woh bhi is webinar ko attend kar sakte hain.

Zoom meeting ki link :
https://us06web.zoom.us/j/84468528892?pwd=RENUMVh5NnBWNEQzMXo3S0xMVlJZUT09
https://chat.whatsapp.com/Hw0lvP4bgw98XXaXGp9m7A


Created a whatsapp group for the webinar.

To make sure that the session joining process is smooth and to communicate in case of any technical glitches.

The webinar is tomorrow.

Pls join if interested in attending.
Reminder for today's meeting ๐Ÿ‘†