We used to use a few months of data. But the amount of information now available from a plethora of sources and platforms has made us think twice about whether the analysis we used to do should be considered a good analysis or simply an investment strategy. That being said, we’re in the period in which the best strategies are likely to be developed and executed, meaning, once those are released to the masses, we’ll probably move on to the next best move.
The good news? We still need more data. Our plan is to track the price movements of the most actively traded security for the last several years and use the analysis and trading algorithms to generate the most accurate predictions.
How much information do you need in order to make predictions?
Generally speaking, investors need the following information in order to generate an appropriate investment strategy:
Forecast market conditions. It sounds simple, but it’s not. It requires predicting what a market will look like once the forecast is made known.
It sounds simple, but it’s not. It requires predicting what a market will look like once the forecast is made known. Future earnings forecast (whether this prediction is positive or negative).
(whether this prediction is positive or negative). Past profits or losses.
You can read more about this information in a more academic way by reading an article I wrote in 2014. Read the article to get a more complete understanding of what this information requires and what tools we use to interpret this stuff.
What is the process involved in making financial predictions?
We use an algorithm to predict, based on market conditions, what the value of a security will be in the future. The algorithm then uses this information to create a portfolio of investments, depending on the forecast. This method has many advantages over traditional Forecast Markets like Vanguard, Fidelity, or S&P Capital IQ as:
Less expensive to implement. As shown in the chart, we use an algorithm (i.e. a trading algorithm) to predict in a way that the market actually behaves in the future, instead of the historical value. We’ve used the algorithm to predict stock prices and futures prices, and we only have to create a portfolio with a few assets; it is cheaper as compared to a traditional Forecast Markets where there’s a lot of research required on how the market reacts to particular holdings. There’s also no risk for us in using an algorithm like the one we use — we aren’t using the data, nor are
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