4/20/2023 0 Comments Linkedin stock prince![]() The Null accuracy is inversely related to the forecast period. It’s to no surprise that next day predictions are not much better than the odds of correctly predicting a coin toss (observed by tracking the null accuracy). The longer the forecasted horizon, the more accurate our predictions become. I’ve used 80% of the data for training and 20% for testing. The data contains daily stock information from - current (because I’m on the free plan, the data is always, at least, one week behind). ![]() I have used one of my favorite stocks, Amazon (NYSE: AMZN) to model the algorithm. The training data used in my project was collected from Quandl Database. This has always been a passion topic for me, so here goes nothing… After all I am only following the plethora of algo and speculative traders that continue to exploit the market in the short term. My hypothesis is simple: By mining for patterns in data using supervised machine learning techniques, I can construct a model and trading strategy that beats the market. Lots of research has already gone into figuring out how stock prices move like here and here. The efficient market hypothesis tells us that all relevant information is already factored into a stock’s price, meaning that neither fundamental or technical analysis can be used to achieve superior gains in the short and long-term. I’m a believer that over the short term (under 1 year) stock prices move in wave patterns - understanding these, can help us understand stock price movements. ![]() I’ve tried many different strategies and put a lot of thought trying to come up with an adequate strategy to consistently make money by investing in the stock market. Since my late high school years, I’ve reaped a deep interest in financial markets.
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