[See Description] Programming for Finance with Python and Quantopian and Zipline Part 1

From the creator

UPDATED series: https://pythonprogramming.net/quantopian-trading-strategies-introduction-python-programming-for-finance/ This series has become outdated with Quantopian 2.0. What is going on welcome to a python for finance tutorial video. Just to clarify right out of the gate, a lot of people envision programming as being used solely for high frequency trading, since computers can execute trades faster than people. While that is true, and computers are used for High Frequency Trading (HFT), they are also used for a whole lot more in finance. We're going to show the use of programming for things like simple algorithmic trades like moving average crossovers, all the way to utilizing things like machine learning. Computers can be used for really anything from high frequency trading to long term investing. Computers allow you to test all of your ideas through what is called back-testing. Back testing is where we take our trading strategies and apply them to historical data to see how they would have done if we had employed them. Back testing comes with some inherent flaws. First off, the usual warning about historical results are not indicative of future ones, and back testing also tends to ignore things like execution time, or how long it takes to actually make a trade. Depending on execution time and the order size, you're almost certainly to experience what is called skid / slippage. Skid/slip is the change in price during an order, from the point of execution initi

Published 2015-06-26 · Watch on YouTube ↗
Availability and playback restrictions are controlled by the original channel.