Summary:

How does the current Gold and Silver market compare to past bear markets?

Gold mining shares down 41% in 3 months.

Gold drops 12.54% in 3 months.

Silver plunges 22.93% in 3 months.

Source: TheDailyGold.com

Historically Gold has had its struggles. Understanding historical bear markets and price ranges gives a clearer picture to the way an algorithm works. By aggregating historical data the algorithm can create a forecast with a predicted confidence level (predictability indicator) using ranges of previous price depreciations. While people excuse themselves into believing gold has many market applications (conductor, art, tooth fillings), an algorithm sees it as an asset with a value (just like a stock, ETF, or Interest Rate), for that reason the algorithmic forecast is completely unbiased. Illustrated in the chart above is the theoretical range (about 1000-1100) at which gold will unlikely fall below; however, historical drops are just data, and we could witness history being rewritten soon.

Prices of various assets within the Precious Metal sector have gone down a lot over the last rolling quarter or 3 month period, in particular Gold Mining shares, which are currently down 41% over the last 90 days. This is an astoundingly large drawdown, only second to the Global Financial Crisis of 2008.

Now more than ever it is crucial to be on top of the precious metals market, a depreciating price offers many market opportunities. While people constantly claimed that gold should rebound and cant drop any farther, the I Know First Algorithm has consistently forecast a price drop. People who avoided buying into gold or sold gold would have saved a loss of 12.54% in the last 3 months alone. Some investors even short the stock, and enjoy making gains off the bearish gold market.

Source: IKnowFrist Forecast August 7th, 2014

The picture above illustrates the position of gold and silver on the heat map (both in red), predicting a price depreciation. Silver went down by 22.98% in just 3 months; the heat map demonstrated how the algorithm was more confident about the silver price drop than the gold price drop (0.37 vs 0.33 predictability signals). The reason XAU and GLD are separated into different forecasts (even though GLD will always have the same price as gold) is that the algorithm recognizes them as two different assets allowing an investor to enjoy two predictions with two confidence levels on the same asset.

However, the true algorithmic success story was the I Know First forecast from Thursday morning (November 6th, 2014) before market opening, which had a bullish signal for both Gold (XAG – 39.09) and Silver (XAU – 24.05). The precious metals since then changed direction and earned 2.73% & 2.48% respectively.

Source: Thursday Morning (November 6th, 2014) Gold and Silver Forecast.

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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