-
Learn more about our analytics for different asset classes, including S&P 500, AGG, and EEM!
-
Our analytical approach is responsive, accurate, and predictive.
-
Our briefs clearly outline predicted trends and provide concise investment insights.
We created a web application with investment price predictions across asset classes utilizing regression and an underlying mean-inversion philosophy, incorporating R, HTML, CSS, and Javascript.
Our basic investment approach is intelligent mean-reversion analysis. We believe that the best assets to invest in are those that demonstrate an upward long-term trend; have a downward short-term trend, though depreciation has recently ceased (by mean inversion, these asset prices are at their trough, making now the optimal time to invest); and are undervalued, as determined by historical analysis and comparison with other markets. To accurately identify these assets, we analyze long-term trends (over the last two years), short-term trends (over the last month), and interrelationships between various asset classes.
Future forecasts are made by examining momentum (short and longer-term trends as assessed through regression) and whether the assets are currently overvalued or undervalued (evaluated by comparing current circumstances to long-term regression and trends). Long-term and short-term regression combined give a nuanced picture of the asset price trends and allow intelligent future forecasts where the degree to which short and long term analysis are incorporated into the prediction varies according to the amount of extrapolation (e.g. 1 month will emphasize short-term trends, 2-yr will emphasize long-term trends) and statistical confidence in trends inferred from regression data.
Log in or sign up for Devpost to join the conversation.