If you want to learn something, but colleges are just charging upwards of $100k for it, do the following:
1/ Go to the program website of each of the top prestigious college known for that specific niche.
This could be Wharton/Harvard for MBA Finance, CMU/Stanford for CS, etc.
2/ Check their program curriculum.
There will be minimum pre-requisite courses to be taken.
There will be course codes for each of those courses.
Type "course code with the name + Curriculum" on Google.
You'll most likely find the syllabus.
3/ Check what all topics are there in the Syllabus.
Check what reference books and text books are prescribed.
Study those topics with those books.
Complement your study with online courses.
4/ Maximize for practical skills.
You'll most likely be able to find assignment summaries also.
You can find and use them to do the assignments also.
5/ The above is the traditional way.
With a little bit of street-smarts, you can put together your own curriculum from the curriculum of the top institutions to maximize for practical and real world skills.
Once you do that, study. Evaluate yourself by how far you go.
• • •
Missing some Tweet in this thread? You can try to
force a refresh
1/ In this thread, I'll cover the things you do regularly during trading in terms of **execution** and how to approach execution from the perspective of automation.
But that is only because you are attuned to it and you don't pay mindful attention to the sheer number of actions and decisions you take throughout the trading day, in terms of execution.
The following are some of the actions you do.
3/ Once your strategy says you've to put on a position
- you pick the relevant scrip to put on a trade
- you decide the required qty/lot size to trade
- based on the signal, it has to be a buy or sell order
- based on the strategy, it has to be a market or limit order.
1/ The first step in automating your trading is defining whatever steps you're doing manually.
I just roughly sketched out some of the actions I do on a regular basis manually.
2/ When designing an automated trading system, it helps to write out the list of things you do during the trading hours, and design a scalable, reusable system accordingly.
This calls for functional or object-oriented programming to be put into use.
3/ Before you design the system, you write everything down in simple English language.
This helps clarify what all minutiae are involved.
A step you consider very small and intuitive, takes a lot of effort in reality to think in code.
This is a raw output of the one lot backtest I did on one of the strategies I trade currently.
Essentially after all the optimisation and out of sample testing I want to look at the performance of the system holistically for the last 10 years.
This starts with a one lot test.
After that, I test for scenario where I'd use the equivalent of maxDD amount to compound each lot and scale the system.
If I test that, the risk of ruin is higher (as at some point you get wiped out having only max DD amount per lot, and facing the same maxDD)
These tests are very optimistic in it that they assume FILLS at the exact price point (which may not be possible). So, there are calculations to be made after this step.
That said, you see 2017? That's when our account got wiped out in this manner of scaling 1 lot per maxDD amt.
Here's how writing can be leveraged to build an audience online:
1) Write a long form essay, publish it in your blog. 2) Convert that to a Youtube video series, as a talking head video or an illustrated presentation 3) Convert all the filmed videos to audio, publish as podcast.
4) Get the highlights from the essay, publish as tweets. 5) Create quotes in the form of illustrations/images, publish on Instagram and Facebook. 6) Extract highlights of the video series, publish on TikTok. 7) Extract those highlights as audio, and publish as byte-sized podcast.
8) Publish the long-form essay as downloadable PDF/ePub in exchange for people's email. Build your email List. 9) Publish independent sections of the essay as tweetstorms/threads. 10) Publish these threads as short essays on medium and other distribution platforms.