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The Natural Gas Index is designed to measure the performance of highly capitalized companies in the natural gas industry involved primarily in natural gas exploration, production, natural gas pipeline transportation and transmission.

I Know First has successfully predicted the price of the AMEX Natural Gas Index throughout the past 10 months and has a strong track record tracing back even further, by analyzing fundamental variables such as volatility, volume, and short-term trends. The Chart shows the algorithm’s predictions for the past 10 months.

XNG stock  forecast from December 13th 2012 till September 10th 2013.

The forecast is based on the 90 days prediction of “I Know First” predictive algorithm.

In general, natural gas price is a function of supply and demand.  Several factors affect the supply and demand for gas and tend to affect price. The main factors are:

• Strength of the economy
• Temperatures
• Interrelationships between fuel markets (Natural Gas, Oil & Coil).

I Know First has accurately predicted the trends in the NYSE Arca Natural Gas Index (^XNG) over the past 10 months.

About 30% of U.S. electricity is generated by natural gas. Hotter than usual temperatures can increase the demand for air conditioning, which in turn, proliferates the power sector’s demand for natural gas, thus increases prices. Moreover, due to the interrelationship amongst oil and Natural gas markets, when prices of oil fall, there is a reduction in natural gas demand pulling natural gas prices downward.  Conversely, when prices of oil rises, relative to natural gas prices, people tend to switch from oil to natural gas, increasing its use and pushing natural gas prices upward.

Both factors have their implication in Natural Gas prices movement. For example, In July, when USA announced a possible attack in Syria, Oil prices increased considerably, pushing demand for Natural gas up and boosting then natural gas prices. By tracking the flow of smart money from one market to the Natural gas market, the I Know First algorithm has accurately recommended a constant long signal on ^XNG between June and September 2013. When US adjudicated against a Syrian strike in August, price for oil decreased, pushing down natural gas demand and price.  At this time, tracking the flow of money from the natural gas market to the oil market, the algorithm advised a short position in September 1^st 2013.

In addition, the United States experienced hotter than usual weather during this period, increasing natural gas demand and subsequently natural gas price. This may also explain the increasing flow of money getting into the Natural gas industry during the summer, provoking a long signal by the algorithm.

If one would have followed the I Know First prediction, they would have gained 16.29% from the first “ buy” signal on March 7^th 2013 until the first “sell” signal on April 18^th 2013 and receive a 4.54% return from the fourth “buy” signal in June 13^th 2013 until the second “sell” signal on the 1^st of September 2013.

I Know First: Daily Market Forecast provides the most accurate and paramount investment foresight based on sophisticated self-learning algorithms to build superlative investment strategies.  Our market forecasting system predicts more than 200 markets: stocks, world indices, currencies and commodities. Enhance your portfolio by visiting us at www.iknowfirst.com or www.gold-prediction.com and www.currency-prediciton.com

 How to read this chart?

Each point on the chart was taken from the actual daily forecast published the morning before the next market open. The chart shows the actual price in thick blue. The positive or negative (Up or Down) signals of the forecast were added to the actual last known price at the time of forecast to result in signal lines. Thus, when the signal line is above the actual line, it means “buy,” if below, it means “sell”. The green and red arrows show what would be the best times to enter the market. The widely ranging signals are scaled relative to the previous average signal range to bring them into manageable scale to fit them all in one chart.

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