Practical Metrics for Financial Time Series

Creating an Investment Decision Framework

https://en.wikipedia.org/wiki/Binary_black_hole

There are various statistical metrics, generated from time series, that can be used, as an aid, in the investment decision process. This article will attempt to capture the essence of the goals and use cases of various metrics as it relates to making investment decisions.

I was particularly interested in writing this because I want to build a reinforcement learning pricing algorithm. The few examples I have seen online have implemented it incorrectly. I thought having a thorough understanding of potential metric would be a good start. I also think that these metrics could be helpful in a semi-automated notification system.

Table of Contents

1. Investment Decision Framework
2. Properties of Time Series
3. Order Book Financial Metrics
   - Bid/Ask Spread
   - Volume Weighted Averaged Price (VWAP)
   - Stock Return
   - Log Return
   - Realized Volatility
4. Technical Analysis (Charting) ;)
   - Stochastic Oscillators (Momentum)
   - Money Flow Index (Volume)
   - Bollinger Bands (Volatility)
   - Moving Average Convergence/Divergence (Trend)
5. Sentiment Analysis
6. Conclusion
7. References