The beginnings of trading

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It’s already been 4 years since I began my first investment through Robinhood. Mostly, the decision was driven by creating profits to live off from. But through time, my idea of investing is converging into growing the money, and managing it than to eat it.

My first couple of failures come from following financial Gurus such as Tim Sykes and Ricky Gutierrez, and we can’t forget about StockTwits. They do have some good trading rules, but all in all does not prove sustainable in longevity. There are huge money management risk and slippage when trading. It’s not so simple to just buy and sell at anytime if there’s no liquidity.

Then there comes me experimenting with high money leverage through options. How I put it is being exposed to 50x the move of a stock. Day trading those were a pain, especially if there is risk of running out of trades below the $25,000 margin requirement. Gains were always random, and so are losses. There is really no way of telling how much one can earn or loss. So that’s why I came across quant investing as the next step.

I’m still a novice in the quant world, but there is one thing certain: one can be a little bit more confident with historical performances and returns when looking into data. I like to have more control in what my money can do and be a little bit more confident in the expectations of money growth. Just giving money into a money pool and letting it do whatever it wants is something I’m just as comfortable with. That’s why I want to start learning about quant investing.

One of the key takeaways from reading a lot of research papers and courses and books is that one can use many sources of data and efficiently use that information to make informed decisions to invest. There is no need to individually read the sources when the code logic can do it for me.

As a scientist, this is a scientific methodology to implement. This is what I’m mostly comfortable with and will continue to learn until I find something.

Just some downsides though, there is so many factors to extract and experimentation. It’s like being friends with a lab rat because you spend so much time failing until finding something that works. One of the textbooks I read had this same ordeal: working on 10 different research projects just to find one that works, but only has a lifespan of one to two years. Then, it fails. One person was able to make $5k into $500k in a year, so it can be worth it.

Again, we don’t know. Only we have is stories. They say this business is secretive. That’s why we don’t hear about it that much. Eventually I may make it, and then befriended with many other algorithmic traders. To be honest, that can be a very good book to make. I should call it, “the underman” or “hidden men”.

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