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Lipa Roitman

Lipa Roitman

Entrepreneur, algorithmic trading system developer.Co-founder of I Know First :Daily forecast for stocks, commodities and currencies based on predictive algorithm.http://iknowfirst.com/Gold prediction based on predictive algorithm.http://gold-prediction.com/Expertise:18…

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Exxon Mobil Stock Forecast: 2 Prediction Methods

We all like to discuss the relative virtues of one stock vs the other. What is missing from many of the discussions is the precision. When you talk earnings estimates, can you compare one analyst's estimate to another's? What is it the quality of their data? Considering that many of the estimates are based on subjective assumptions, it is not a surprise that they diverge greatly. Most of the time, "to the surprise of pundits, numbers continue to be the best system for determining which of the two things is larger."

Case in point: Exxon Mobil

This year Exxon Mobil Corporation XOM has been outperforming the competitors, the British Petroleum BP. and Chevron CVX. However, recently Exxon Mobil reported third quarter revenues were down 7.7% on the year. The reasons quoted are global economic uncertainty that continued in the third quarter with further weakness in Europe and Japan. On the other hand, the China growth rate decline has moderated. And on the positive side the lower upstream volumes were partly offset by stronger industry refining margins. Earnings from the downstream operations have doubled.

Cutting to the Chase

With all the contradictory data in the report it is easy to get lost trying to put a precise value on XOM. Today, is XOM a buy or sell? Could anyone tell? Is it even possible?

Exxon Mobil is one of the world's largest companies by revenue and one of the largest publicly traded companies by market capitalization in the world. The company is ranked number 1 globally in Forbes Global 2000 list in 2012.

We will show here that even such widely watched stocks can be predicted successfully using at least two different methods. The market is too involved to be totally efficient. Even the largest companies are subject to price inefficiencies which can be exploited by those who can read the signs.

XOM stock made two large moves this year:

Case 1. In a recent one it climbed 20 percent from the bottom price of $77.6 on June 5, to a peak of 93.48 on October 18, before pulling back to 89.88 by October 24.

Case 2. Previously after a peak of $87.04 on May 1 the stock began to fall and continued downhill till the bottom on June 5.

We will consider these two moves separately, but first let's look what the insiders did.

Valuation by Insider Actions

Looking at insider actions, I found two big sells by the XOM VPs at the end of February, and one on May 1, at the peak! While most of the time the insiders' actions can't predict the market moves, it was different here.

This is a big company operating an established business. Except for the new oil field finds, the effects of every other factor on the business valuation model is known and measured. It surely has good accountants who daily update the spreadsheets. These guys knew what the company is worth. And they sold again in September. That should have put you on notice! And soon afterwards the stock dropped back to the August trading range.

The company releases operating data only a few times a year. And their spreadsheet formulas are still secret. Then what the investor to do in between?

Now let's see if the price of XOM that everyone's eyes are always watching it, could be predicted by advanced numerical computations.

Valuation by Algorithms.

The market valuation process for each stock is based on dry numbers, such as cash flow, debt ratio, profitability (EBITDA), but as these numbers are absorbed by the market players, they begin to acquire dynamics of their own. As they interact with other information about other stocks, they form patterns and waves, like the waves and streams in the ocean. The money is constantly moving between thousands of investment venues looking for better return. Thus all the markets are interconnected and what happens in one market affect the rest.

The I KNOW FIRST stock forecast system is based on measuring and predicting the market waves. The model is a 100% empirical self learning algorithmic system, meaning it is based on historical data and not on any human derived assumptions. The human factor is only involved in building the mathematical framework and initially presenting to the system the "starting set" of inputs and outputs.

The system monitors and forecasts over 150 equities, stocks, indexes, currencies and commodities. Among them it issues daily crude oil forecast.

Among energy related commodities in I KNOW FIRST system are Brent Crude oil, USO Future Contract On Wti Crude Future),  Chemicals Index CEX and XOI oil and gas index,, natural gas index and nuclear energy.

Among oil companies are XOM and ConocoPhillips COP Royal Dutch Shell plc RDS-B Russian Lukoil LUKOY and Brazilian Petr PBR . Some solar stocks are also included.

he chart below (Fig. 1) presents the system actual performance on XOM price prediction. It shows the 90 day forecast. The thick blue line shows the actual price. The thin broken red line on the chart is the signal line. The positive or negative (up or down) signals of the forecast were added to the actual last known price at the time of forecast. Thus, when the signal line is above the actual line, it means "buy", if below, then "sell". Each point on this chart was taken from the actual daily forecast published in the morning before the next market open. Each forecast consists of six forecasts for six time horizons, from three days to one year ahead.

XOM Chart, 90 Day Signal Line
Case Study 1. June 5 to October 18 XOM Climb.

(See right side of chart in Fig. 1)

XOM began showing a weak up signal at first in the 90 days time horizon in I KNOW FIRST stock forecast on June 2, then a stronger signal on June 29, then by mid July it was already signaling loudly the upcoming uptrend in the shorter term forecasts. A detailed analysis is here.

I was looking for publications about XOM around that time. Interestingly, at the end of June three articles appeared praising XOM:

•    "Exxon Remains A Solid Long-Term Buy"
•    "Exxon: The Safety Stock For Oil Price Drops"
•    "Buy Exxon Mobil: High Dividend Yield And Cheap Valuations"

Case Study 2. May 1 to June 5 XOM Downtrend.

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(See left side of chart in Fig. 1)

At the beginning of March XOM gave two strong down signals in 90 days and 30 day forecasts. After the stock was meandering mainly sideways for a while, the down signal returned in mid April in a 90 day forecast. By the end of April it was confirmed by other shorter horizon down. After the peak of $87.04 on May 1 the stock began to fall and continued downhill till the bottom on June 5.

Forebodingly, on April 30, just before the plunge, one article had a headline: "4 Big Reasons To Avoid Exxon Mobil Now". Thus the signs were there. Others could read them, not only our algorithms.

Conclusions

Various ways of stock analysis, both fundamental and numerical, can give a good estimate of stock direction.

In the case of well run companies the insider buys or sells can give a good guideline of the company's current worth.

What's next for XOM?

In the long term Exxon Mobil is highly correlated with the Dow Jones Industrial Index DJI (DIA) and with the Consumer Index CMR (IYC).
It has an impressive record of increasing revenues, raising cash dividends and its total assets keep growing. As it grows it increases investment in R&D.

Exxon Mobil's Cash Dividends per Common Share

It is planning a multibillion-dollar petrochemical expansion at its Baytown complex, looking to take advantage of the country's increasing supply of natural gas. With this it begins to diversify its downstream products, getting into competition with the Dow Chemical (DOW). As the basic economy gets better, and it will, and the consumers will start spending, the XOM will do even better. All of us need gas.

By. Lipa Roitman, PhD


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