I thought the smartest minds in finance decided you cannot forecast stock prices, and, specifically, you cannot forecast the direction of the market.
Information and Price Dynamics predicts high and low stock prices over periods such as a day or several trading days. This is not exactly the same as predicting the price of a stock at a particular time in the market day. The best forecast of Microsoft’s stock price (MSFT) in tomorrow’s trading session at 11AM, for example, is the current price of MSFT. On the other hand, we can say with some confidence what the high price for MSFT is likely to be tomorrow. The same goes for the probable low price in tomorrow’s trading session. Our ability to do this is related to measuring the recent variability or volatility of MSFT prices.
I’ve heard of predicting volatility, but how does measuring the up and down variability of stock prices help you their future direction?
Our company has developed technical stock price indicators built with forecasts of high and low (H/L) stock prices. These help predict open and closing prices for one or several days forward, supporting trading systems which key off the signals of these stock price indicators. In effect, what we are saying is that the profitability of these trading systems is proof of our capability of predicting the direction of stock prices.
So, you make a lot of money off this capability to “beat the market”?
Information and Price Dynamics develops robo-trading applications to implement trading systems in its company trading account. Thus, real-time trading validates our approach, but we are not a hedge fund. We are primarily a predictive analytics company. So, we are looking for partners in deploying trading systems using our proprietary methods of predicting high and low prices.
If you have only been trading recently, how do you know your systems are robust, how do you know they can be profitable over the long term?
We perform extensive “back-testing” using “trading simulations.” One of our principals published a paper illustrating a simple, profitable trading simulation with the popular exchange traded fund SPY. The forecasts of today’s high and low prices are essentially equal to the previous trading day’s high and low prices. These “forecasts” support profitable swing trades which beat a passive investment approach by a significant factor in a trading simulation over more than ten years.
Predictions utilized in trading simulations have to be tested “out-of-sample.” Thus, the forecast approach may be optimized over a “training” period. Then the profitability of this predictive approach is explored in “test” periods – price history which is are not in any way connected with how the forecast method is produced. Often, this boils down to developing forecasts over rolling data histories and applying these forecasts on a one-period-ahead basis. The crucial point is that you cannot “smuggle the future” into the predictions if you want to be honest in evaluating their efficacy.
Bottom-line, Information and Price Dynamics trading simulations show significant gains can be made over passive investment approaches.
Can you provide an example?
One of the most powerful IPD price indicators is the Combined Growth Indicator or CGI. Here are trading simulations with recent price data utilizing CGI’s.
Over a period 2017 to 2021, for example, long and short trades with the biotech stock AMGN achieved more than double the cumulative gains from a passive or buy and hold investment strategy. This reflects margin trades that are made generally safe and profitable from the high win/loss ratios of the trades. On average, trades are entered or exited for AMGN every 12 trading days.
This looks good. How can my investment group explore some of these approaches?
Information and Price Dynamics can provide your company with an API which will link you to the forecasts and trading signals you need. We suggest a Test Phase of one to two months involving a setup fee. After validating profitability, you transition to longer term contract or purchase of intellectual property (IP) directly – including perhaps forecast methods and indicator construction.