SCALAR ANALYSIS (S.A.) IN FINANCIAL TECHNICAL TRADING. A View of the Markets in a Different Angle. By Ramoncito D. Ulep, CTA/CPO Investment Advisor

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1 Page 1 of 13 SCALAR ANALYSIS (S.A.) IN FINANCIAL TECHNICAL TRADING A View of the Markets in a Different Angle By Ramoncito D. Ulep, CTA/CPO Investment Advisor FXA USA 40 Wall St. 28 th Floor New York, NY United States Tel.: (213) info@fxausa.com Website: July 25, 2012

2 Page 2 of 13 TABLE OF CONTENTS Page Title 3 Introduction 3 Definition 4 Examples of Price Scales 6 Methodology 9 Retracements 11 Sample Probability 12 Retracements Observation 13 Summary

3 Page 3 of 13 INTRODUCTION The purpose of this paper is to define and explain Ramoncito D. Ulep s (Author) method of Scalar Analysis in Financial Technical Trading, particularly the observation of the movement of prices as they pass from one scaled point to the other. Chart examples are illustrated to further explain how the method is used. (Table Of Contents) DEFINITION Scalar Analysis in Financial Technical Trading is a type of Technical Analysis, which utilizes the scaled values of financial securities and derivatives. One of the most common scale values is the price scale, which ranges from zero to infinity. Other common scale values are volume, period and other technical indicators all of which make up a contemporary financial technical chart. Most participants in the financial market use price scales in their analysis as a basis of market valuation. Although prices of both securities and derivatives sometimes swing in extreme ranges, their values remain observed and recorded periodically (i.e., monthly, weekly, daily and hourly). These prices tally the total position valuation of all the participants in the financial market. The age of computers (a.k.a., the digital age) brought these data to where it is now possible to record price values as they are traded. These plots are called ticks 1, the smallest increment a security or derivative can move. With these streaming data come tick-by-tick technical charts, which are almost instantaneously created for all participants to see and analyze. These charts can be viewed either through paid subscriptions provided by financial institutions and data providers, or available free via the Internet the difference varies in the quality of data and the service they provide. (Table Of Contents) 1 "In financial markets, a tick size is the smallest increment (tick) by which the price of stocks, futures contracts or other exchange-traded instrument can move." - Source: Wikipedia

4 Page 4 of 13 EXAMPLES OF PRICE SCALES Below are chart examples of linear price scales of widely observed financial securities and derivatives: Figure 1-1: The Dow Jones Industrial Average daily candlestick chart with a 200- point price scale ranges from $10, to $13, from September 22, 2011 to December 7, Figure 1-2: EUR/USD (Euro against the US Dollar) 4-hour candlestick chart with a 25-pip price scale ranges from $ to $ from October 15, 2012 to December 20, 2012.

5 Page 5 of 13 Figure 1-3: Gold s weekly spot market candlestick chart with a 50-point price scale ranges from $ per ounce to $1, per ounce from November 4, 2007 to December 20, (Table Of Contents)

6 Page 6 of 13 METHODOLOGY One way of analyzing financial charts using Scalar Analysis is by observing price values as they move from one scaled marker to the other. By setting up the charts in fixed scales (e.g., in increments of 50, 100, 200, 500, 1,000, etc.), one can establish a set or sets of random variable 2 probability events 3. Figure 2-1: Gold s weekly spot market candlestick chart with a 200-point price scale ranges from $ per ounce to $1, per ounce from October 31, 2004 to June 4, Random Variable is a variable whose value is subject to variations due to chance. Source: Wikipedia 3 Probability Event is a set of outcomes to which a probability is assigned. - Source: Wikipedia

7 Page 7 of 13 Figure 2-2: Ulep s Scalar Analysis can be best understood by plotting dots on the chart where the price touches the scaled points, and then connecting them with lines (see Figure 2-3 below). Figure 2-3: Together with the gridlines, the dots and the lines simplify the entire chart into data where simple random variable probabilities can be established.

8 Page 8 of 13 Figure 2-4: The numbers on this S.A. chart represent each count the price touches the markers. In this example, the price went up 8 out of 12 times from point 0, which yields a random variable probability of 67%. (Table Of Contents)

9 Page 9 of 13 RETRACEMENTS It has been observed throughout history that, in most cases, the prices of securities and derivatives tend to rise and fall overtime due to the buying and selling of market participants. These actions create peaks and troughs in the charts. Counter trends to the larger trends are known as a retracements (see Figure 3-1 below). Figure 3-1: This US Dollar Index chart shows the counter trends or retracements going against the main trend, which is bullish from 1995 to While the existence of counter trends are unquestionable, the probabilities of at which levels the prices would retrace back to depend on very wide variety of both technical and fundamental factors. Because of this, there are a lot of uncertainties on these probabilities. As a rule of thumb, in a technical perspective, professionals use either technical line indicators or studies, such as the Fibonacci Retracement 4, or look for previous levels where values pause at its current trend (up or down) then bounce off or reverse. These levels are called supports and resistances, or tops and bottoms, and become probable targets for analysts forecasts. 4 "Fibonacci Retracements use horizontal lines to indicate areas of support or resistance at the key Fibonacci levels before it continues in the original direction." Source: Investopedia

10 Page 10 of 13 Figure 3-2: This chart shows the most common Fibonacci Retracement levels (38.2%, 50% and 61.8%) of the US Dollar Index from early 2002 to mid-2013 Figure 3-3: This chart shows the supports and resistances of the US Dollar Index from mid-1998 to mid-2013 (Table Of Contents)

11 Page 11 of 13 SAMPLE PROBABILITY Upon observing a S.A. chart, one may notice the many different combinations of calculating random variable probability events that may be used for forecasting and trading. An example of which is counting the number of times the price went through the marker moving to the next, and another is counting the number of times the price bounced off the marker back to the previous point (see Figure 4-1 below). Figure 4-1: This US Dollar Index S.A. chart yielded 18 breaks and 20 bounces (almost equal the number of times, or probability), therefore, one may assume that the more times a certain event (e.g. a break) happens, the higher the chance the opposite will happen (e.g. a bounce). The reason for this is that the price will always try to achieve the probability at hand, which is (Table Of Contents)

12 Page 12 of 13 RETRACEMENTS OBSERVATIONS One of the most profound and remarkable retracement probabilities that has been recorded by the Author while observing the S.A. charts is a phenomenon where the price goes back to the most recently broken support and resistance markers with very high probabilities at least, until such time that the security or derivative cease to trade or significantly declines in trading volume. Albeit some professionals call these events, retests, there are neither exact nor estimated probability calculations that are available as guides to be used in any analysis. Ulep s retracements consistently yield a random variable probability of more than 55% in all of the observed charts 5. Figure 5-1: Gold s spot market S.A. daily chart with a 50-point scale beginning from $950 per ounce, from September 2009 to June 2013, shows 10 out of 13 (77% yield) markers were retraced. It also shows that 3 out of the first 5 resistance markers (points 2, 3, 4, 5 and 6) were retraced. (Table Of Contents) 5 The observed charts used have 10 or more probability events. These charts include the major currency pairs (USD/CHF, EUR/USD, GBP/USD and USD/JPY), major US indices (Dow Jones Industrial Average 30, S&P 500 and NASDAQ 100), and Gold and Silver spot prices.

13 Page 13 of 13 SUMMARY Ramoncito D. Ulep s method of Scalar Analysis in Financial Technical Trading is achieved by using equidistant or scaled basis points in the charts as markers. The observation of the movement of prices (or other values) within these markers create multiple probability events in the random variable space, thus, providing the user additional information which can be used for analysis in trading the financial market. Ulep s Retracement involves prices in the S.A. charts going back to the most recently broken support and resistance markers. This retracement observation yields a high random variable probability of more than 55%. (Table Of Contents)