Gold has been in a bear market for well over a year now. Over the last two years, the price of gold has fallen from close to $1,800 per ounce to under $1,200. I Know First is able to predict how the price of gold will change over a future time period using a state-of-the-art predictive algorithm. The impartial algorithm capitalizes on the inherent predictability of the stock market resulting from short-term uncertainty, irrational human behavior, and differing fundamental asset valuations.  It separates the predictable part from stochastic (random) noise.  Then it creates a model that projects the future trajectory of the given market in the multidimensional space of other markets.

Using the algorithm along with some independent research can help investors make wise decisions when considering buying or selling gold. The algorithm works better in the long term, as the predictability of the stock increases over longer time periods. The algorithm gave gold a signal strength of -8.69 and a predictability strength of 0.25, correctly pointing out an opportunity for investors to short the commodity over the one-month time horizon.

A Bearish Gold Market – When the Reality Meets the Algorithmic Forecast

On November 7^th, gold had fallen to a four and a half year low, and gold’s value decreased 4.34% over the month period ending November 17^th. In each algorithmic forecast, there is the signal and the predictability indicator. The signal strength indicates how much the current price deviates from what the system considers an equilibrium, or “fair”, price. The signal can have a positive (predicted increase) or negative (predicted decline) indication. The heat map is arranged according to the signal strength with the strongest long signals at the top, while the short signals are at the bottom. The table colors are indicative of the signal. Green corresponds to the positive signal and red indicates a negative signal. A deeper color means a stronger signal and a lighter color equals a weaker signal. The predictability strength measures the importance of the signal. The predictability is the historical correlation between the prediction and the actual market movement for that particular market.

The fundamental factors causing gold to lose value are the success of the stock market and the US Dollar. Gold is viewed as a risk free investment against riskier interest bearing assets. Economic optimism could cause investors to spend their money is riskier assets such as equities. A robust US economy could also prompt the US Federal Reserve to raise interest rates, hurting non-interest bearing gold. The Dollar has remained in favor as US data points to an economic recovery, causing the price of oil to decrease. This also hurts gold, often viewed as a way to hedge against oil-driven inflation. Many analysts are recommending shorting gold at this time. While these signs point to a continued bearish market for gold, what is truly impressive about the algorithm is it is able to predict periods where investors can long the commodity in short periods when it gains value.

Source: www.nasdaq.com

Algorithmic Recent Success Story – A quick win

In this forecast, the algorithm was able to accurately predict an increase in the value of gold over a one-week time horizon. On November 7^th, the algorithm gave gold a signal strength of 26.67 and a predictability strength of 0.14, correctly predicting that the value of gold would increase over the following week.

Get Today Gold Forecast based on predictive algorithm

Gold subsequently climbed to a two week high on November 14^th, yielding a gain of 4.15% to investors who used the algorithm correctly. The price of gold increased due to struggling Japanese and European markets, as the Japanese Yen reached a seven-year low and the Ruble continues to struggle. It was further helped as investors who attempted to short gold were forced to sell their shares at a loss, further increasing the value. While these factors led to a slight rally for the value of gold, they might not last as the strong US Dollar and economy far outweigh these factors, especially if the US Federal Reserve does in fact raise interest rates for the first time in eight years.

Algorithmic Analysis (Explanation) 

I Know First is a financial services firm that utilizes an advanced self-learning algorithm to analyze, model and predict the stock market. The algorithm produces a forecast with a signal and a predictability indicator.  The signal is the number in the middle of the box. The predictability is the number at the bottom of the box.  At the top, a specific asset is identified. This format is consistent across all predictions.

Signal Explanation

This indicator represents the predicted movement direction/trend; not a percentage or specific target price. The signal strength indicates how much the current price deviates from what the system considers an equilibrium or “fair” price. The signal strength is the absolute value of the current prediction of the system. The signal can have a positive (predicted increase), or negative (predicted decline) sign. The heat map is arranged according to the signal strength with strongest up signals at the top, while down signals are at the bottom. The table colors are indicative of the signal. Green corresponds to the positive signal and red indicates a negative signal. A deeper color means a stronger signal and a lighter color equals a weaker signal.

Analogy with a spring: The signal strength is how much the spring is stretched. The higher is the tension the more it’ll move when the spring is released.

Predictability Explanation

This measures the importance of the signal. The predictability is the historical correlation between the prediction and the actual market movement for that particular asset, which is recalculated daily. Theoretically the predictability ranges from minus one to plus one. The higher this number is the more predictable the particular asset is. If you compare predictability for different time ranges, you’ll find that the longer time ranges have higher predictability. This means that longer-range signals are more important and tend to be more accurate.

Source: Example of an I Know First algorithmic heat map.

In this particular Top 10 Stocks Forecast from November 27th 2013, XOMA had the strongest 1-month signal but did not have the strongest predictability. As the asset is in a deeper green color box, this indicates that the algorithm is very bullish.

The algorithm does not only predict the strongest signals, but also the weakest. If this is a market bubble the algorithm will be able to shift its prediction to a strong negative one, allowing investors to make gains on both the price appreciation and depreciation (by shorting the stock).

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