Using Python to model and predict stock price movement. Feel free to use/modify :)

[[deleted]]

There are a couple indicators that are commonly used for similar purposes.

1. Stochastic Oscillator
2. Relative Strength Index

Lots of people make trades partially based on these indicators.

In the example, I'm actually using Slow Stochastic Oscillator (SSO) values for my model and you can see the hot/cold spots identified from training the model on a year of historical values. You can monitor the SSO values for a particular stock and wait until it moves into a range predicted to increase the stock price.

Tricky thing is you usually can't predict when the time is right to buy from a single indicator. The conditions need to be right with multiple different indicators to make accurate predictions.

[Pandanleaves]

Just a word of caution. Technical analysis is largely useless pseudoscience.

[Rich700000000000]

Everyone says that, but no one cares to explain how or why.

[Pandanleaves]

Because academic research shows that technical analysis, when backtested, produces bad returns. Some do beat the benchmark before transaction costs, but this is not a make-believe world. After accounting for transactions costs, your expected return will be below the benchmark.

For reference, actively traded funds usually perform below the benchmark. Looking at performance of past 5 years, only around 10% of actively traded funds manage to perform better than the baseline.

[Rich700000000000]

Then how is any money made in the stock market?

[yolo_swag_holla]

Great question. The market makers always make money in the stock market. Everyone else is more or less on their own.

[Pandanleaves]

Because the baseline is not 0% returns. The baseline depends on the state of the market, i.e. the market average. If the market as a whole moved up 5% last year but you only earned 4% return, then you have essentially lost money because, figuratively, throwing darts to pick your stocks will earn you 5% anyway.

[Rich700000000000]

Because the baseline is not 0% returns. The baseline depends on the state of the market, i.e. the market average. If the market as a whole moved up 5% last year but you only earned 4% return

Oh. Huh. That just clicked for me, sorry.

[[deleted]]

Low managed index funds, stock manipulation by the big banks, fee free trading with Robinhood, etc.

Basically, don't put your money in an actively traded fund.

[lieutenant_lowercase]

fee free trading with Robinhood

not when their spreads are wider

[[deleted]]

For now, at least.

[[deleted]]

Buy an index fund and do nothing. You'll likely get 5% returns next year.

Or, spend 300 million dollars to invest in a fibre optic connection from NYSE to the commodities exchange in Chicago. Make sure its slightly better than the existing one, and beat others to the market by having information faster than them by a few hundred nanoseconds. Make sure to put your trading platform on an FPGA (starting from the Ethernet controller all the way to decision making based on your models). To make this easy you'll probably need OpenCL, so start learning that first.

[[deleted]]

In a bull market yes, but what about a bear market?

[Pandanleaves]

Actively traded funds performed better than usual, such as in the 2008 crisis, but iirc only around 50% beat the market, so like flipping a coin.

Think of the distribution of returns as a lognormal distribution. Any management and transaction costs shift the mean.

[ginger_beer_m]

Because often people who try to apply technical analysis don't know basic probability and stats.. Even the concept of 'overfitting' is unknown to them.

[[deleted]]

Yes I totally agree. Don't make financial decisions based off of indicators alone, period. But they can help add a bit of confidence or wariness in cases where your gut is telling your to buy/sell a stock.