market timer user guide

MARKET TIMERTM USER GUIDE

The Ultimate Market Timing Tool For Market Timer Version 5.4.4 Revised 3 March 2019

MARKET TIMER USER GUIDE

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INTRODUCTION What Is Market TimerTM? Market Timer is a set of proprietary algorithms that measure supply and demand and the movement of financial market participants to provide unparalleled insights into short, intermediate and long-term stock market movements with a high degree of accuracy and confidence. Market Timer is delivered as a spreadsheet, updated each day, in the client Portal along with actionable comments and daily signals. Market Timer measures and quantifies real supply and demand in the market. It can actually visualize the herding activity of market participants on the major stock market indexes. We created the algorithms that track institutional algorithms Algorithmic trading by computerized systems rule the markets today. Market Timer exposes the buying and selling activities of market participants on public exchanges from the retail trader all the way to the institutional trader. It does this by using proprietary supply/demand and a volatility algorithms to identify buying and selling activity at a high level. It then uses that information to pinpoint high probability swing points and market anomalies that lead to predicative market scenarios. Over 25 years of testing, improvements and proven signals The proprietary algorithms that generate the signals in Market Timer have been developed over the past 25 years, so this is not new or an unproven tool. The original developer of the spreadsheet discovered that there were high, positive correlations between certain internal market data and the closing prices of the DOW Industrial Average and the S&P500. Those correlations have remained stable for more than two decades. We have since added a spreadsheet for the NASDAQ Composite index. Internal market data correlations are examined in a first layer of data and refined in algorithms on multiple layers to extract daily signals. Intra-day signals are available using our studies for TDAmeritrade’s ThinkorSwim platform. (Some scripts are also available for Trade Station (v10) and NinjaTrader (v8) too). Quantify supply and demand in the markets Our algorithms allow our clients to quantify supply and demand, visualize positive or negative herding and track, what we have determined to be institutional buying and selling giving us a powerful look inside what’s really happening in the market unlike any software, charting tool, trading system or quantitative method available anywhere.


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The correlations, relationships and anomalies on the spreadsheet is what drives our analysis and provides key insights into actual supply and demand in the markets. Why Market Timer? The reason Market Timer was created was to give traders an edge in the market that was not based solely on price action. We call it ‘data-driven technical analysis’.

Data-driven analysis avoids ‘blind spots’ in traditional chart-based technical analysis. 99.9% of traders analyze the markets for trading purposes using ‘price smoothing’ via MACD, stochastics, moving averages, Bollinger Bands, etc. but that’s not what moves markets – price tells you what happened, not what will happen.

The market moves as a result buying and selling activity. That demand (buying) and supply (selling) is driven by market participants who herd in the direction of what they perceive to be the ‘majority’. Humans, as a group, feel ‘safe’ in crowds and follow crowds they have an affinity with. It’s basic human nature – we don’t want to be left out of the group.

As Market Timer’s, we know what the crowd is going to do before it does it. We don’t predict price, we predict the behavior of the crowd that moves the market. We see into market internals, ‘behind the curtain’ if you will and position ourselves ahead of the winning crowd – bull or bear.

Who uses Market Timer

Market Timer is used by professional traders, investment advisors, hedge funds, institutional traders, family offices, prop traders and retail traders who want to dramatically improve their bottom line investment and trading results. Key to Market Timer’s Success There's a famous hedge fund, Renaissance Technologies, founded by the legendary mathematician James Harris Simons who made billions in the market. He is extremely quiet about his quantitative methods and algorithms used. In a rare interview (you can find it on YouTube) he says that his algorithms have one purpose: To find market anomalies and capitalize on them. This quote from a New Yorker article is especially interesting to us, “Renaissance has had an unprecedented run. Bloomberg Markets, in an article last year, called the firm’s signature product, the Medallion Fund, ‘perhaps the world’s greatest moneymaking machine.’ For nearly three decades, it has gone up by eighty per cent annually, on average, before fees. Renaissance’s other, bigger funds have done less well. Simons said that this is a consequence of their size: large amounts of money cannot be traded as quickly, and longer-term trading makes algorithms less useful. ‘It’s like the weather,’ he says— ‘the nearer in, the higher the certainty’.“ That is true of Market Timer signals too, “the nearer in, the higher the certainty”.


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What Data Does It Require To Generate Signals? The Market TimerTM spreadsheet uses just five core internal market data points that can be manually updated daily or intra-day (or automated using our studies for TOS). Those five data points generate subsets of data used in the algorithms to generate Market Timer signals. Using only these five data points for each version of Market Timer provides powerful insights. Over time, we discovered which data points were the most critical, most efficient and most effective in generating actionable signals that correlated to future movement and direction of the herd (predicative values). The data used in Market TimerTM is simple to update on your own - just five pieces of data are required daily to update the spreadsheet and generate the MT signals (intra-day updates can also be helpful). Those five data points for each version of Market Timer are: NYSE/Nasdaq Advancing Issues NYSE/Nasdaq Declining Issues NYSE/Nasdaq Advancing Volume NYSE/Nasdaq Declining Volume Price Change of the DOW Industrial Average®/NASDAQ Composite Index Manually Updating the Spreadsheet

There are two websites that publish the NYSE internal market data that we recommend:

http://markets.wsj.com - Just scroll down the page until you see "US Stocks - > Market Diary" and select the NYSE data for Market Timer.

Enter the data in unlocked Columns A to F (Nasdaq) and A to G (NYSE) on the spreadsheet(s).

http://www.mcoscillator.com/market_breadth_data/ - If you're missing more than day of data, you can download a few weeks of internal market data there. On the right side of the page you'll see a link for "Daily Oscillator Data". The spreadsheet you download will contain the last 6 months of NYSE internal data and DOW closing values that you can copy and paste into the spreadsheet. The only thing it does not do is calculate the DOW Change, which is done easily by copying the DOW closing prices into a spreadsheet and manipulating the data to retrieve the change.


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Introduction The overriding major concepts in technical analysis also apply to the analysis of the signals generated by Market Timer:

1. strength/weakness 2. support/resistance 3. overbought/oversold 4. trends (up/down, short-, intermediate-, long-) and 5. anomalies/divergences

Trend time frames are defined as follows: Short-term – trends lasting minutes to hours to a day. Intermediate-term – trends that generally last 2-7 days or more. Long-term – trends that last months or years.

Signals Generated by Market Timer Central to Market Timer’s power in predicting market participants behavior (referred to affectionately as the ‘herd’) and price movements are the MT signals. There are 5 primary signals generated by Market Timer’s algorithm: • MT Supply/Demand Index (MTSD) • MT Volatility Index (MTVol - which includes Pipeline and Flow indicators) • Balance of Power (BoP – visualization of bull/bear herding + BoP Curve indicator) • Swing Signal Algorithm (Up/Down swing signals based on our algorithm) • Strength/Trend Index (ST - strength/weakness indicator of a price move) There are two supporting indicators that are also important confirmations used occasionally in our analysis: • Average Volume per Share (AVS, column “X”) • 21 vs 27 Day SUM (DOW) or 11 vs 21 Day SUM (NASDAQ) Lastly, there’s one MT indicator we use to identify pricing anomalies on the DOW: • Price Anomaly (Column “CM”) The terms we use and some of the concepts may be unfamiliar to you, but they are extremely powerful and worth your time reviewing. If you have any questions after studying this Guide, please contact support at the bottom of this page: https://strongmarket.com/portal


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HOW TO READ MARKET TIMER Measure, Quantify, Track Supply & Demand and Herding of Financial Market Participants Let’s start with the primary Market Timer indicators:

MT Supply/Demand Index

We quantify market supply and demand of the herd through our proprietary Market Timer Supply/Demand Index (MTSD) and the direction of the herd through the Balance of Power (BoP) section of Market TimerTM

MTSD is the measurement of the supply/demand liquidity and the amount of risk (on or off) assumed by market participants that are herding

The MTSD Index gives us a specific positive (buying / liquidity) or negative (selling / removing liquidity) number EOD. It can also be use on an intra-day signal to determine the intensity of moves made by the market during the day session using the Premium SD script for TOS. The amount of selling or buying pressure on the market for any particular day is typically in a range small range - between +10 to -10, but in cases of extreme herding behavior it can go outside these ranges possibly indicating climax buying or selling signaling the end of a trend.


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It can also alert us to unusual market activity. We can tell if the herd is starting to buy or sell by watching the MTSD numbers. Two useful MTSD signals are the ‘buying on the decline’ and ‘selling on the advance’ as illustrated below. Example #1: Buying on the decline

When the DOW declines but the MTSD index is positive it indicates what we call ‘buying on the decline’. In the chart above, the DOW declined -9.64 points but the MTSD was +9, the next day it declined -53.50 and MTSD was +4, the day after that the DOW declined -11.77 and MTSD was +5. This is ‘buying on the decline’ which means that there was net buying by the bullish herd on these days, not selling, even though the market declined. The result was the market rallied by 483 points in the 5 days following the accumulation.


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Example #2: Selling on the advance

When the DOW advances but the MTSD index is negative it indicates what we call ‘selling on the advance’. In the second example, we see a large, negative MTSD Index at -328 and the next day at -4 on when the DOW moved higher by 72 points and 37 points. The result was the market declined by 2,326 points in the 5 days following the distribution. The MT Supply and Demand Index is a powerful indicator that informs us if there’s net real demand (accumulation) or net real supply (distribution) coming into the market. The MTSD signal should be used in conjunction with the MT Volatility Index and the BoP to give us an accurate picture of the overall trend. Example #3: MTSD Index Identifies Accumulation/Distribution The MTSD Index can also tell us, with a high degree of confidence, if stocks are being accumulated or distributed long-term. In this Guide we use the term “accumulation” to mean that the herd is buying and once the buying is strong enough stocks with rise. We use the term “distribution” to mean the herd is selling stocks and when the selling is strong enough stocks will decline. From December 30th, 2015 to February 11th, 2016, the DOW was in a steep decline losing more than 2,000 points. For the casual market observer this was a difficult time to trade. The market was volatile and selling appeared to be relentless. Then the market dropped 756 points in just 5 days. However, it was clear to us that the decline was at an end when we looked at the declines and very small negative MTSD numbers on 2/9, 2/10 and 2/11 it indicated the selling was drying up:


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A MTSD Index number equal to or greater than 10 indicates heavy buying (accumulation) or less than or equal to -10, heavy selling (distribution). Anything in between is considered and noted as “moderate” (4 to 9) or “light” (0, 1, 2 or 3) for either accumulation or distribution. We can clearly see the selling starting to dry up on 2/11 with the DOW declining -254 points but MTSD was only -8 indicating “moderate” selling. The following three days we see heavy accumulation (2/12, 2/16, 2/17) with MTSD readings of +14, +15 and +18. In this example, the DOW climbed nearly 4,000 points over the next 12 months. Although this one indicator alone can dramatically improve our trading, we have additional MT tools that are designed to confirm, support and verify our analysis of the MTSD Index. In other words, MTSD should be used in context with our other indicators. Together they give us a complete picture of the state of the market.


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MT Volatility IndexTM (MTVol)

This proprietary index measures the shift in the herd when buying to selling or selling to buying is taking place on a daily basis. It can also be use on an intra-day signal to determine the intensity of moves made by the market during the day session using the Premium MTVOL script for TOS.

MT Volatility is our barometer for the overall market. When it’s above 100% we are in bear market territory. When it’s below 90% we are in bull

market territory. The area between 90% and 100% typically means a choppy, trend-less market.

Ø The average bullish range for MTVol is between 50% - 90% (buying activity).

Ø The average bearish range for MTVol is between 100% - 150% (selling activity) MTVol measures the net balance of buy/sell orders in the market over a period of time. An index reading under 100% means more people are buying than selling. An index reading over 100% means more traders sold or sold short. The trend and rate at which moves matters as much as the level. Here are some examples: If MTVol is 70% and rises to 80% in a week, there was net selling by market participants for that period. If it rises by 10% over a day or a few days, it’s even more significant, and may indicate more selling to come.


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If MTVol is 90% and declines to 80% in the period of a week, there was net buying by market participants. If it declines by 10% over a day or a few days, it’s even more significant and may indicate more buying to come. KEY POINTS: When MTVol is trending lower and is below 90% it indicates optimistic buying and generally any selling is light, pullbacks will not last long and the market will soon resume its advance if there’s no strong bearish herding in the BoP. When MTVol is trending higher and is above 100% it indicates negative fear and selling and generally any buying is light, rallies will not last long and the market will resume its decline if there is no strong bullish herding in the BoP. TIP: The trend of MT Volatility is as important as the level. Watch for increases or decreases in MTVol of 10 net percentage points or more in a single day. It’s a clue that there’s momentum behind the move and it will likely continue in the direction of the increase or decrease.


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MT Pipeline and Flow

The Pipeline and Flow are secondary indicators to help predict MTVol.

The MT Pipeline is our ‘early warning system’ to potential increases or decreases in MT Volatility. It uses an algorithm based on the movement of

the MT Volatility Index to predict when MTVol might experience a change in value.

In the example below, the Pipeline indicated four days before that MT Volatility would drop below 100%:


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Flow is the average of the 3 columns of the Pipeline so we can quickly see the probability that MT Volatility will rise or fall in the near future. When the Flow is higher than 90% it senses that MT Volatility could rise in the near-term, the cell values will turn red. When the Flow is below 90% it senses that MT Volatility could decline in the near term the cell values turn white. The cells in the three columns of the Pipeline will fill red when they rise above 90% and turn white again when values drop below 90%. Pipeline Trends, Levels and Anomalies The Market Timer Pipeline helps to warn of us of future movements of MTVol. The trend is as important as the level it's at and so even though it may be ‘flashing red' it's the trend as well as the level of the Pipeline that has predictive value. The Flow is the average of the three Pipeline columns, so it gives us a quick glance at the trend of the Pipeline. When the Flow rises above 100% it gives us a heads up to the potential for the MTVol to also increase above 100%. When Flow declines below 90% we anticipate that MTVol will also decline below 90%. When that does not happen then we consider it to be an anomaly and something worthy of study.


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Balance of PowerTM (BoP)

Our Balance of PowerTM (BoP) signal tracks the movement of the herd and shows us who is in control (buyers or sellers) at any one time. It can also be use on an intra-day signal to determine the intensity of moves made by the market during the day session using the Premium BoP (with bull and bear trap signals) script for TOS.

Balance of Power (BoP) is a unique visual representation of the herd moving through the market

The ‘herd’ includes every market participant (retail, HFT, prop traders, investment advisors, institutional traders, hedge funds, family offices, trust and pension funds, etc.) that moves through market and whose transactions are recorded and published by the exchanges. We see evidence in our BoP signal that the entire market is driven by this herding effect and we can actually observe the "shift" (see screenshot below) taking place from one side to the other as the herd moves through the marketplace:


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As mentioned, the Balance of Power is a visual representation of the herd moving through the financial markets. The “1’s” in the filled cells are simply representations of herding activity and do not carry any other significance. In other words, we could have used “X’s” or “0’s”, etc. or any other mark. The BoP is 12 columns in width and divided evenly into a Bullish and Bearish herding sections. The six on the left are for visualizing bullish herding. The six on the right are for visualizing bearish herding. An idealized structure, for either bullish or bearish herding, starts in the furthest left column in the respective sections and fills out into the rest of the columns from left to right as shown here: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 As the cells are ‘filled out’ from left to right, the ‘perfect’ bullish or bearish herding increases until it reaches the farthest right column.

Ø TIP: Only the strongest herding will fill out all six columns from left to right in the stylized manner above or something similar.

This is the perfect structure but, of course, the market is anything but perfect. But when you’re trying to evaluate the potential extension of a rally or decline or trying to determine if the rally or decline is coming to an end look to the perfect model above as the key. You will never see this form perfectly as shown above in real trading situations. Herding in the BoP can be stalled, be a non-starter or be ill-formed which all provide important information about the rally or decline in progress. This may be the most challenging of the MT Signals to analyze but it’s also the most important to determine possible starting points and ending points and the strength or weakness of a rally or decline. In almost every case, you will always want to see at least the first three columns filled out to confirm a new rally or decline – as a start. This formation generally leads to the best declines or advances with the biggest swing in prices. This is a ‘perfect’ bearish herding example of how a decline should start if it’s going to be a large swing:


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This is a ‘prefect’ bullish herding example of how a rally should start if it’s going to be a large swing:

And, of course, there are some exceptional rally’s or declines that didn’t start this way but this is the ideal way they should start.


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BoP Curve

What interested us and the reason we named it the BoP ‘curve’ is because the formations remind us of a bell curve.

The BoP Curve is similar to what the Pipeline and Flow are to MTVol – it’s helps us see what is coming in the BoP - when it reaches extreme low or high levels (‘valleys’ and ‘peaks’) and when it potentially starts a new

herding ‘cycle’

We noticed a cyclic motion in the Balance of Power (BoP) from bullish herding to bearish herding and back again. We started thinking about why that might be happening in the market and began working on an algorithm that would show us this phenomenon in a visual way each day. Also available in the Market Timer Premium scripts download for intra-day use. The result of our work is the BoP Curve. The bearish herding on the Curve is highlighted in blue and the bullish herding is highlighted in the beige just like the BoP bullish/bearish columns. The difference is that we can now ‘see’ when there are peaks and valleys in the curve and which way the BoP (bullish or bearish) is trending – up or down.


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Swing Signal Algorithm

The Market Timer Swing Signal Algorithm (MTSS) is an intermediate-trend (2-7 days or more) signal that generates a green arrow for an UP trend, a red arrow for a DOWN trend and a dot (•) for a transition between up and down signals or neutral signal.

The Swing Signal algorithm is a powerful prediction algorithm based on a quantitative analysis of Market Timer data that provides an indication

of price trend and typically turns up or down before a move happens

The Swing Signal is available on both the NASDAQ and the DOW/S&P500 spreadsheets.


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Strength Trend Index (ST) The Market Timer Strength Trend (ST) indicator is a short-term and intra-day signal that helps determine the intensity of market movements by the herd.

The ST number is generated by a quantitative analysis of Market Timer data that measures momentum, speed and recency of internal market data

to determine the intensity of the move.

We look especially for ‘divergences’ from previous lows and high and the strength number to determine probabilities. It can also be use on an intra-day signal to determine the intensity of moves made by the market during the day session using the Premium ST script for TOS. This is the benchmark we use internally to determine if a move is ‘strong’ or ‘weak’: DOW POINTS ADVANCING STRENGTH BENCHMARK 0 to +100 <1 +100 1 +200 2 +300 3 +400+ 3+ DOW POINTS DECLINING STRENGTH BENCHMARK 0 to -100 <-1 -100 -2 -200 -4 -300 -6 -400+ -8+ If the price move and corresponding STRENGTH indicator number is the same as or less than the benchmark then it’s considered to be a ‘weak’ move. If the price move and corresponding STRENGTH indicator number is the same as or more than the benchmark then it’s considered to be a ‘strong’ move. In addition, as you’ll see in the examples below ‘divergences’ can give you an edge by setting up the next trading day. Let’s look at some examples:


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In the example above, we first note that there’s a dip in the Trend chart moving right to the left indicating that ‘dip’ is fading into past history… and so the trend since the dip has been ‘up to sideways’. Next, we look to see if there’s movement of the Strength (higher and “stronger” or lower and “weaker”) from the previous day. In this example, we see that the Strength has moved higher from -3 when the DOW declined 344 points to “-0” when it declined 9 points. That’s a move higher indicating the market is getting ‘stronger’. This gives us a clue that there’s at least a probability of a rally the very next day because the market is getting ‘stronger’ according to the reading in the Strength column. The result? The market advanced 254 points the next day. Here’s another example of how we use the Strength indicator, and divergence, to predict the next day’s market move:


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In this example, we had one day when the market moved lower by 166 points with a “Strength” of -0 showing mild weakness. That was followed by two days in a row in which the market moved higher and the Strength indicator moved higher from +0 to +3. The very next day however, the Strength indicator declined from +3 to +1. Here’s where the divergence can help: DOW CHG STRENGTH +347 3 +399 1 (weaker) When the DOW is higher than the previous day but the Strength indicator is lower, that shows that the move wasn’t as strong as the previous day which indicates weakness - even though the gain in points was larger. The very next day the market declined 299 points. Using the same example, the next four days, the market declined. However, our Strength indicator went from -15 to -6 to -1 showing some Strength coming into the market as it moved closer to zero. The very next day the market declined 70 points but the Strength indicator rose to +1. Also note that the Trend chart started moving higher on the days in which the market declined -381, -420 and -70 points. The next day the market advanced 336 points. Here’s an example of using the Strength indicator with divergence:

The DOW had two large declines in one week but the selling was less than ½ of the previous large decline. The DOW declined 1175 points and the Strength indictor was -224 showing a lot of selling intensity. The next time the DOW declined 1,032 points the Strength indicator was -58. The selling was less intense. While this does not mean the market will go higher the next day, it’s a signal that the intensity of the selling was not as strong as the previous 1,000 point decline as we should look at the next day’s opening for an opportunity to go long. The next day the DOW advanced 330 points.


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Long-Term (LT) Signal

The LT Signal is based on our observations of Market Timer indicators and uses the BoP at the core of its calculation. The LT Signal ranges from +3 to -3 with the zero line being the point at which we move from “bull market” to “bear market”. Bull markets are on the +(plus) side and bear markets on the – (minus) side. Just like MTVol, the trend is just as important as the level. When the LT Signal trends on the +(plus) side of zero line we are in a bull market. When the LT Signal trends on the -(minus) side of the zero line we are in a bear market.

Similar to MTVol, the trend of the LT Signal is just as important as the level. If it’s moving higher, the market will generally move higher, if it’s

moving lower, the market will generally move lower

This new long-term algorithm (LT Signal) looks at longer-term trends of the market – typically 6 months to one year.


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Benchmarking the Long-Term (LT) Signal: The following grid may be used to benchmark and evaluate the market using the LT Signal levels and values: LT Signal Value Indication Action +2 to +3 Strong bull market Long +1 to +2 Bull market Long +1 to 0 Weak bull market Caution 0 to -1 Weak bear market Caution -1 to -2 Bear market Cash or Short -2 to -3 Strong bear market Cash or Short


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Market Timer Model Time Frame Comparisons Here's how our current Model's compare to the three trends mentioned in the beginning of this Guide: SHORT-TERM (intra-day or next day): MTSD and Strength indexes (SD/ST in TOS): Intra-day to a one-day trend. Updated daily on the spreadsheet. A signal can be used intra-day or used at the close which indicates the next day bias – UP or DOWN. INTERMEDIATE-TERM (3 to 5 days): BoP and Swing Signal algorithm: 2-7 day trends. Updated daily on the spreadsheet. LONG-TERM (months or years): Long-Term (LT) algorithm signal. Typical move lasts 1 month to 1 year or more. Updated daily in the spreadsheet and charted weekly in the Insights newsletter.


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Market Timer Columns & Insider Tips We read Market Timer from left to right – just like we read the newspaper. Ignoring the Date column, we will start with the Average Volume per Share (AVS) and move left to right on the spreadsheet to the LT Signal and the Price Anomaly, column CM, (not shown below).

Let’s take a closer look at each column:


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(1) Average Volume per Share (AVS) The Average Volume per Share or AVS column is simply the total NYSE or Nasdaq volume for time period divided by the total number of shares traded that day. We make a mental note of its level. A normal range is 1000 to 1500 (x1000) on the NYSE and 650 to 950 on the Nasdaq (x1000) at the close of trading. The NYSE it usually only goes above 2000 when there’s a lot of volatility in the market like the period from April – June 2010:

Note: If the AVS is over 1500 the cell is highlighted beige or if it falls below 1000 it is highlighted green. ----- The AVS usually only goes below 1000 when it’s near a US holiday (Christmas, Easter, Thanksgiving, New Year’s etc.) or when trading is light during the height of the summer vacation period in July and August. The only time AVS becomes useful as an indicator of future price action is when the market has been in a steep decline for some time and then suddenly finds a ‘bottom’ at which time it starts to decline from 2000+ levels to normal levels mentioned above.


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This gives us an indication that volatility will likely decline, and the market may be ready to enter a new bull phase. Of course, we look for additional confirmation from MT signals before taking any action. (2) SPX / Dow Change Instead of looking at the level of the DOW we simply note the price change for the day positive or negative. We chart the level of the DOW with our LT signal which is included in each weekly Insights newsletter. (3) MT Supply/Demand Index (MTSD) If MT Volatility is our barometer for the market environment (bullish or bearish), then MTSD is the mercury. MTSD is the measurement of the supply/demand liquidity and the amount of risk (on or off) assumed by market participants. In other words, the more bullish the herd is the higher MTSD will register. The more bearish the herd is the lower MTSD will go. Extreme reading +100 or higher or -100 or lower sometimes indicates a new trend or the end of the trend – must be analyzed in the context of MTVol levels and BoP. (4) MT Volatility (MTVol) Mentioned above, the trend is as important as the level of MTVol. Watch the trend – is it higher or lower over the last 3-7 days? What level is it at? Under 100 over 100? Sharp increases or decreases (5% -10% or more in a single day) sometimes signal a change in trend of the herd. (5) Pipeline Provide ‘advanced’ MTVol data on whether the herd is moving toward selling or buying. Watch the ‘3rd column’ as most MTVol trends start there… ‘seeing red’ in the third column typically means there are pockets of seller starting to herd in the market and MTVol will start rising… when it turns from ‘red’ to ‘white’ in the 3rd column it typically means we are starting to see pockets of buyers herding in the market and MTVol will start declining.


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(6) Flow As mentioned above, FLOW is the average f the Pipeline columns so in a single glance it can inform us of what MTVol might do in the next few days or weeks. But we’ve also created a very basic ‘trading system’ around the FLOW column (see below). We watch for ‘bottoms’ – typically in the 40%-60% range and peaks in the 150%+ range. (7) Balance of Power (BoP) The BoP is how we ‘visualize’ bullish and bearish herding moving through the markets. We use it to see if there’s more bullish or bearish herding for a given period of time, look at herding trends, identify anomalies such as ‘long tails, and ‘bull’ or ‘bear traps’, ‘orphans’ and more (see below). We also look to see if the herding is ‘spotty’ - meaning that some columns are filled in while others are not. This typically happens when the bullish or bearish crowd lacks conviction and alerts us to a potential reversal or the end of a trend. Below is an example of ill-formed bullish herding and ‘spotty’ gaps which gave way to strong bearish herding:

When we do our daily analysis, we look for ‘well formed’ herding. If we don’t see well-formed herding then we can deduct that the bullish or bearish herding is weak. We also look to see if the herding on one side or the other is ‘thinning’. Thinning is when the only herding is in the 5th and 6th column (counting from left to right) on either side of the BoP.


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Here’s an example:

In the example above, the bullish side of the BoP started to get ‘thin’ (restricted to the 5th and 6th columns) setting up the ‘bull trap’ and possible take over by the bears. (8) BoP Curve The newest of the indictors for Market Timer, the BoP Curve gives us an idea if the BoP will see bullish or bearish herding in the future.


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BoP Bullish Curve When the bullish curve is rising it indicates we will see price rise as well and see more bullish herding. When the bullish curve is declining it indicates there’s a temporary decline in bullish herding and there could be a pullback in prices. BoP Bearish Curve When the bearish curve is rising it indicates we will see prices decline as well and see more bearish herding. When the bearish curve is declining it indicates there’s a temporary decline in bearish herding and there could be an advance in prices.


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(9) Strength Trend Index (ST) As stated above, ST helps determine the intensity of market movements. It’s a our ‘momentum’ indicator. When we do our analysis, we check the reading to see if it’s outside the benchmark ranges. If it is it sometimes indicates a move in that direction could start a new trend. (10) Swing Signal Algorithm The Swing Signal algorithm is sensitive to shifts in the market typically before they happen. Often, we will see the Swing Signal turn ‘up’ or ‘down’ a few days before we see the market turn. We want to see if the Swing Signal algorithm changes direction or turns ‘neutral’ at important market swing highs and lows. (11) DOW Cycle Points: 21 vs 27 Day SUM’s


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We use a 21 Day vs a 27 Day SUM optimized cycles for the DOW. Rather than an average, we add each day’s net price change to the last for 21 days cumulative and 27 days cumulative and compare them on the graph. We chose the 21 days and 27 days based on our market cycle studies. You’ll see our Cycle Points analysis occasionally in the Insights newsletter when it gets to extreme levels. We like it because the SUM’s provide real-time price action data, without smoothing. Price average indicators such as moving averages, stochastics, MACD and other price average indicators smooth price action and lag the market. These studies can give us a better indication of overbought/oversold conditions in the market using real-time price data without lagging or smoothing. (12) LT Signal Our Long-Term Signal algorithm can identify important market tops and bottoms. When doing our analysis, we look at the rate at which the signal is increasing or decreasing. If it starts moving sideways with little to no progress in either direction it can often point to a change in market direction. (13) Price Anomaly and Price Expected Price Anomaly is also the difference of the Dow Price Change and the Price Expected but it’s expressed as an absolute value. In other words, the difference is always a positive number. We made it an absolute number because it’s not important if it’s positive or negative only if it is a small or large number as described below. Price Anomaly (PA) measures the elasticity of prices based on our Price Expected (PE) algorithm. The PE predicts what the price change should have been based on the data we input on the spreadsheet. When the PE and the actual price change in the index is out of alignment the PA is ‘stretched’ causing a spike like the one’s on the chart below and the response is typically a ‘snap back’ in the opposite direction for prices. The majority of large PA’s come on declines, but not always. A normal ‘level’ of the PA is ≤100. A level under 100 means that the internal market data and prices are positively correlated or in ‘alignment’. Anything ≥200 is a significant ‘stretch’ and a ‘snap back’ is anticipated. A PA level between 100 and 200 is still significant but has fewer ‘snap back’ success. When prices are declining, and volatility is high the PA can be stretched daily and that’s why we often see the market up by 400 points one day and down 400 points the next which we call a ‘snap back’.


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We asked the question, “Is there any way to anticipate these ‘snap backs’ during periods of high volatility?” Let’s see…

The example above shows the DOW advancing +673 points on 3/23 and the PA was 280. This indicated a ‘snap back’ could be anticipated. The PE algorithm based on the internal market data we entered into the spreadsheet said the prices should have been up 393 points not 673 so the move was out of alignment with the PE and the market needed an ‘adjustment’ in prices. The ‘adjustment’ of prices that are out of alignment with the data meant that prices would, in this case, ‘snap back’ by declining. A ‘snap back’ is always opposite direction of the day in which the PA occurred. The next day prices declined -344 points. In the same example above we see a second instance of a ‘stretch’ and ‘snap back’ – this time in reverse starting on 3/29. The Dow declined -458 points, but our PE algorithm indicated the price should have been lower by -1100 points. The PA was 641, a very high number. Another ‘snap back’ could be anticipated. In this case the Dow would ‘snap back’ the next day by going higher. The next day the Dow went up +389 points. In the next example below from 4/18 to 5/2 we see that prices were declining, for the most part, but the PA each day was less than 100. This indicates that prices are in alignment with the data and no snap backs are likely to occur. This is simply normal price action and the data and the PA algorithm are aligned.


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Using PA to anticipate ‘snap backs’ in high volatility market environments provides us with another critical tool for trading success – and can sometimes ‘forecast’ the next day’s change.

In the example above at point “1” we see a PA of 141. We got a ‘snap back’ the next day and the DOW declined 301 points. At point ‘2”, we also see a high PA… this time with a reading of 177. The next day the DOW advanced 171 points – almost the exact PA reading of 177 from the previous day. It’s infrequent but sometimes a ‘price projection’ of the next day’s closing prices could be forecast using the previous days PA reading. RE: ‘DOW Price Expected’ Column We get a lot of questions about the “Price Expected” column to the far right in the spreadsheets - mostly from those who want us to ‘predict’ the next day’s closing values! But the column is simply the price change that the DOW should have made that day according to the algorithms predictions based on our model.


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We do not use the column as a signal. The purpose of the calculation is to act as a 'self-correcting' correlation algorithm for our signals. In other words, it's a dynamic adjustment for the algorithms that generate the MT signals. The result is we are always correlated to the market and we don’t have to manually correct or adjust our algorithms based on changing market conditions.


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INSIDER TIPS and TRADING SETUPS: Major Advances There are four things we watch for when reading MTSD before a major rally takes place: At the end of a decline we watch to see if there are two or more days in a row or within a few days in which: (1) MTSD is over 10 and/or AVS is over 2000, (2) DOW price change is over 100 points, (3) Flow falls below 110% and there’s evidence of (4) Bullish herding in the BoP. A good example is November 2016 just after the US Presidential elections:

Even if you waited until after all the signals fell into place, the gains would have been significant as the DOW climbed over 9,000 points in about 14 months. MTSD can also alert to a climax indicating with the end of a trend or the beginning of one.


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Massive Selling Climax Before Multi-Year Advance This is the largest MTSD reading (-2,073) we have in the MT database – that day it happened was within 150 points of a bottom that resulted in a nearly 8+ year market advance. We attribute the large negative number to capitulation/climax of selling pressure.


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Large Selling Before Decline In this example we see large selling (-328) before the market declined 2,326 points in just 5 days:

Major Declines All market declines of any significance have started with an increase in MT Volatility above the 90% level.

Ø TIP: If a decline fails to push MTVol above 90%, and there’s little to no bearish herding in the BoP, then the previous rally is likely to resume.

Once MTVol rises above 100%, caution is in order. Sharp declines and large price swings can be expected.

Ø TIP: If MTVol rises above 110% and stays there for two days or more, the chances are a major decline of 5% or more is either underway or about to begin in earnest.

If MTVol reaches 150% or more look for signals that may indicate an end to the decline such as a decrease in the Pipeline and Flow, a decrease in MTSD negative index readings and the dissipation of bearish herding in the BoP.

Ø TIP: Caution is still in order but typically any MTVol reading above 150% would alert you to a potential buying opportunity to be presented soon.


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Pipeline and Flow As stated above, the Pipeline & Flow gives us a heads-up to potential increases or decreases in MT Volatility within days of it happening. But there’s a subtle ‘tell’ or divergence when reading the Flow that may help you time an entry.

If there’s a decline in prices and the DOW and other major indexes are making new lows watch the Flow. If the market makes another new low, watch to see if the Flow is INCREASING in value or DECREASING? In the example above, the DOW made a new low, but the Flow was lower (198%) than the previous reading (222%) … in other words, the Flow was higher but prices are lower (a divergence) setting up a potential long trade. The DOW rallied 1,358 points in the six days that followed.


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SWING HIGH/LOWS USING FLOW and 3rd Column Pipeline We analyzed the peak ‘high’ and ‘lows’ of the Flow to see if they coincided with major market swings and found something interesting. From February 5th to Friday’s close we identified the Flow high and low and highlighted them with a red rectangle. To the right are the identification of the highs/lows and it appears that the Flow HIGH and LOW also coincided very closely with the actual SWING HIGHS and LOWS in the DOW:

Of course, we were only able to determine the Flow HIGH or LOW in hindsight. But we did come up with a ‘tell’ of when the Flow could be hitting a new high or new low. If you look on the graphic above, you’ll see we have a yellow oval on the third column of each HIGH or LOW.


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SWING LOW/Flow HIGH What we discovered was that at a Flow HIGH that 3rd column reading was, on average, about 20-50 points higher than the Flow which coincided with a SWING LOW in the market. So for example on 2/5/18 the 3rd column of the Pipeline was 274% and the Flow was 222%. The 3rd column was 52 percentage points higher than the Flow (note that the bearish BoP was ‘full’):

RESULTS: The DOW advanced 873 points in the 9 days that followed. On 3/2/18 the 3rd Pipeline column was 132% and the flow was 114% - a difference of only 18 percentage points. However, we noted that there was also some bullish herding in the BoP that day:

RESULTS: The DOW advanced 776 points in the 6 days that followed. On 3/23/18 the 3rd Pipeline column was 226% and the Flow was 185% - a difference of 41 percentage points: (note that the bearish BoP was almost ‘full’):

RESULTS: The DOW advanced 984 points in the 8 days that followed.


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At the SWING HIGH/Flow LOW We see percentage differences to be smaller, but we also see the 3rd column percentage too be in the 50%-65% range or lower as well. On 2/16/18 we identified the Flow at 68% and the 3rd column was at 49% - a difference of 19 percentage points AND the 3rd column number was below 50% (note the lack of a ‘1st column, recency bullish herding on the BoP):

RESULTS: The DOW declined 610 points in the 9 days that followed. On 3/9/18 Flow was at 68% and the 3rd column was at 54% - a difference of 14 percentage points AND the 3rd column was 54%. (note the gap’s in the bullish herding):

RESULTS: The DOW declined 1810 points in the 10 days that followed. On 4/18/18 Flow was 66% - the Flow the lowest level in over a year when it was at 64% in Feb 15, 2017 - and the 3rd column was 64% - a difference of just 2 percentage points, but as mentioned it was the lowest level in over a year:

RESULTS: The DOW declined 702 points in 6 trading days.


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DOW vs BoP In this section we’ll look at another DOW relationship, but this time with the Balance of Power (BoP). The DOW/S&P and Nasdaq are inversely correlated to Flow. However, the BoP is positively correlated to the indexes and gives us additional insights into price action. The chart below provides us with some information not available in other indicators (MT or not). To understand the chart better let’s talk a little about how it was constructed. The BoP is assigned ‘+1’ for each cell filled in. The maximum bullish net is +6, the net bearish total cannot be lower than -6. It can’t exceed these levels and so we have ‘upper’ and ‘lower’ boundaries we can use to help us identify peaks, divergences, basing and support areas and trends. We take the total filled-in bullish BoP cells minus the total filled-in bearish BoP cells to get the net total for the day and use that net amount to plot on the chart along with the DOW:

There are three helpful patterns we identified in this relationship to help us with market timing.


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First ‘divergences’ (#1) are a pattern we saw often on the chart and in our historical data. At the far left of the chart you see the DOW rising from the 24750 area to just above 26500 from Jan 4th to Jan 26th. At the same time we see the net bullish BoP decline from approx. +5 to +1. This divergence setup one of the best shorting opportunity in years. The DOW declined approx. 2500 points in 10 days. The second pattern we identified is when we reach a ‘peak’ (#2) in the net values from +6 to -6. When the BoP total is +6 it means that there’s so much bullishness that there’s not likely to be any more bulls willing or able to help the market move higher – everyone is already on board. When the BoP total is -6 it’s not likely any more bears will join the move lower – everyone who wants to be is already on board. The third pattern we see is ‘basing’ (#3). We see basing primary when the market declines and ‘peaks’ and ‘divergences’ at the top of market swings. On the chart above ‘basing’ is easy to see. The net levels on the BoP find a support level and typically will decline to the same level twice or more times before launching a swing rally. 1st Column BoP Importance and Recency

The important thing to keep in mind about the BoP is that it’s a visual representation of herding in the financial markets and when a new rally or decline is starting it always starts from the very first column on the left because it’s the most recent representation of herding activity and as more and more of the herd join in the move it fills out to the right of the BoP section. You don’t need to wait until the first three columns are filled to take a position, in fact you shouldn’t especially when MTSD and MTVol are indicating a move is imminent, but the BoP will confirm the move and, depending on how ‘well formed’ it is, the potential for the size of the move. The image below shows a transition from bearish herding to bullish herding in the BoP. This example is about as good and as near ‘perfect’ of herding as you’ll see in any time period so study them closely. Both of the moves were substantial. The bearish trade started on 9/19/14 when MTVol rose above 100% and we got a “selling on the advance’ signal for the day. We also started to see the 1st column of the BoP bearish section start to ‘fill’.

Ø TIP: The 1st column on either the bullish or bearish side is the most important column in the BoP because it’s the most recent herding impulse. NO significant rally or decline has ever started without that 1st column filling out first.


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From 9/19 to 10/16 the bearish herding as well formed and only a few gaps were noticed in the cells on the bearish side. There were also a few ‘bullish’ herding attempts but as you can see they were single herding formations that never gathered any momentum (followers) and simply died out. A clue that the selling was just about exhausted happened on 10/15: The DOW declined 173 points but MTSD was only -1. In addition, there was no bearish herding in the 1st column that day. For a move that size, with no bearish herding in the 1st column is a signal that the bearish herd was starting to scatter and no longer had the strength to continue. The very next day on the 16th we got a small decline but with a +10 on the MTSD Index! That’s ‘buying on the decline’ – we also got the 1st column of the BoP bullish side filling out. A single 1st column on the bullish side is not enough on its own to generate an ‘UP’ signal for our model but that along with the ‘buying on the decline’ and the previous days readings indicate the market is about to go into rally mode. Once we see the BoP starting to fill out from left (1st column) to right we get a sense that the move could be large:


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Ø TIP: If you follow the 1st column down during the decline and then the rally you’ll see

that many of them were filled out. Filling out those 1st columns as the swing move develops gives you some confidence that the move will not only be potentially large but that it could last for quite a while.

There’s one other thing we look at for potential direction of the market – the number of 1st columns filled because the 1st column is the most important due to recency. In the following example we had 2 days in the 1st column on the bearish side of the BoP and 1 day in the 1st column on the bullish side. So we saw more net days bearish than bullish this week by that measure as illustrated below:

Using this example, we could argue then that overall bearish herding increased this week based on recency of the 1st column BoP despite the fact there were more BoP cells filled on the bullish side rather than the bearish side. An “Orphan”…

Example above: The ‘bear orphan’ indicates that the bears could not form a herd large enough to push the market significantly lower. -----


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An orphan is an attempt by the bulls or bears to push the market in one direction but failed to convince others to join in which leaves a single cell filled in but alone in the BoP. The 1st column being the most recent attempt at herding is considered to be the most important for initial formation of the herd. The herding seen in columns furthest to the right from the 1st column are distant attempts at herding and generally do not affect the market the farther they are from the 1st column. They are important however in our analysis especially when they form ‘bear traps’ and ‘bull traps’ and our longer-term views of the market. Bear and Bull Traps A bull or bear ‘trap’ is a very powerful formation in the BoP that indicates that the market will likely reverse the current day’s move the very next day. A ‘bear trap’ is large space between the 1st column and a cell filled in on one of the 4th, 5th or 6th columns and nothing in between. When a ‘bear trap’ happens it generally means that the market will close higher the next day thereby ‘trapping the bears’. Bear Trap Here’s an example from the week of April 30th to May 4th 2018, and if you look for them there are many examples in the spreadsheet.

A ‘bear trap’ is large space between the 1st column and a cell filled in on one of the 4th, 5th or 6th columns and nothing in between (see Guide for additional details). When a ‘bear trap’ happens it generally means that the market will close higher the next day thereby ‘trapping the bears’. If it happens on the bullish side of the BoP it’s a ‘bull trap’ and the market will generally close lower the next day thereby ‘trapping the bulls’. We saw the bear trap twice this week with gains the next day of 64 points and 121 points on the NASDAQ.


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Bull Trap A ‘bull trap’ is large space between the 1st column and a cell filled in on one of the 4th, 5th or 6th columns and nothing in between. When a ‘bull trap’ happens it generally means that the market will close lower the next day thereby ‘trapping the bulls’.

We saw a bull trap twice in the example above with declines the next day of -178 points and -251 points on the DOW. It’s a Market Timer setup we pay close attention to. BoP ‘Long Tail’ Formation A long tail is when there are ‘1’ markings in the last column of the BoP on the bullish side or bearish side and no other 1’s in any of the other columns. This typically marks the end of the bullish or bearish herding, especially if there’s been trending for an extended period of time. Below is an example from a bullish BoP (period shown: 1/4/18-1/26/18).


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The trend changed at the end of the ‘long tail’ into a bearish herding trend:

Note that at the end of a ‘long tail’, just before the trend changed, there was no new herding in the 1st to 5th column of the BoP.


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Market Timer Data and Long-Term Trends Is there a correlation between Market Timer data to our long-term outlook? And are there any indications that Market Timer can provide to confirm our long-term outlook? We studied Market Timer herding signals, MTVol, MTSD and BoP, data for the years 2009 to 2018 (to-date). A summary of the data is below. Let’s review what we found and see if there’s any conclusions we can draw from it to help us time our long-term trades and confirm our bearish outlook for the year. We posit that financial market participants herd. It’s the theoretical framework for everything we do at Market Timer. But it’s more than theoretical because we see evidence of it daily in the signals and updates. We measure this herding behavior by use of MT Volatility and the Balance of Power (BoP). MTSD doesn’t measure herding, it quantifies the supply/demand in the market as a by-product of herding so we left it out of this analysis until the next section. According to the table below, the net difference (+/-) between the Bullish and Bearish BoP was a prime factor in the direction the DOW took each year. If it was a net positive, there would be gains in the market. If it was a net negative, there would be a decline on the year: BoP AND MT VOLATLITY ANNUAL AVERAGES / DOW Annual Chg: Herding BoP1 MT Volatility1 Year Bullish Bearish Net Diff

+/- MTVol

Ave MTVol

Hi/Lo DOW Pts

+/- 2009 579 272 +307 91% 159/54 +1651 2010 545 272 +273 92% 151/57 +1149 2011 406 338 +68 99% 177/67 +640 2012 432 255 +177 94% 153/63 +886 2013 490 176 +314 91% 135/63 +3472 2014 428 226 +202 93% 143/64 +1245 2015 259 285 -26 102% 129/72 -398 2016 547 154 +393 91% 148/58 +2367 2017 354 83 +271 93% 121/72 +5019 2018 205 79 +126 94% 122/74 -134

1 We took the number of cells ‘filled-in’ in the BoP added them together for all six columns to get the Bullish or Bearish BoP totals for the year and subtracted them to get the net difference. 4 MTVol Hi/Lo are the highest and lowest levels of MTVol that were recorded during the year. 2 A declining MTVol average is bullish, a rising average MTVol is bearish. --- But its MTVol that is the largest factor in the DOW’s net gain or loss on the year and the one that grabs our attention.


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We sorted the data by annual average MTVol levels and DOW price changes for the year:

MTVol Ave DOW Chg/Yr 91% +1651 91% +3472 91% +2367 92% +1149 93% +5019 93% +1245 94% +886 96% -453 99% +640

102% -398 This table tells us what we already know, but it’s a nice reference: Higher levels of MTVol suppress price gains in the market. Very high average levels cause prices to decline. Average annual levels of 91%-93% seem to be the most beneficial MT Volatility levels for price gains for the year. Once we get to 95% or higher prices start to struggle for gains… above 100% prices decline. We continue to monitor the average annual MTVol levels to determine if they are increasing or decreasing in line with our long-term forecast in the OUTLOOK section of each weekly MT Insights newsletter.


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MTSD: By-Product of Herding We examined MTVol and BoP and their correlation to price changes on the DOW annually. We also said, “MTSD doesn’t measure herding, it quantifies the supply/demand in the market as a by-product of herding...” Now we will study the Market Timer Supply/Demand Index (MTSD) data for the years 2009 to 2018 (to-date). A summary of the data is below. Let’s review what we found and see if there’s any conclusions we can draw from it to help us time our long-term trades and outlook. MTSD ANNUAL AVERAGES: Year Average Daily2 DOW Pts +/- 2009 -4 +1651 2010 -12 +1149 2011 -10 +640 2012 +1 +886 2013 +2 +3472 2014 +2 +1245 2015 -1 -398 2016 +2 +2367 2017 +7 +5019 2018 TD +3 +115

2A declining MTSD average is bearish, a rising average MTSD average is bullish. Some observations from the chart above in context of annual market activity: 2009: The early part of the year was weak and the market declined in March then recovered and went higher finishing the year up +1651 points. MTSD average daily was -4 for the year. 2010: The mid-year weakness of 2010 was overcome and the market rose in the second half of the year to close higher by +1149 points. There was an MTSD outlier in 2010. On June 4, 2010 MTSD was -2073 which we consider capitulation. It was within a few weeks of the market low for the year as well. As a result MTSD average was -12 for the year. If we eliminate the outlier, the MTSD average would have been -4. 2011: The first part of the year was sideways to up. The market was weak starting in August and declined until October. The market recovered somewhat but was still weak and closed higher for the year but by just +640 points. Average MTSD was -10 for the year but was rising into the new year.


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2012: The market started well, had some weakness in May and again in October and November and ended the year higher by just +886 points. MTSD average for the year was +1, stronger than 2011, and ended the year positive. 2013: The MTSD strength that started in 2012, carried into 2013 and the DOW ended higher by +3,472 points. MTSD average for the year was +2, an improvement over 2012. 2014: The market had another good year, up +1,245 points but January, July and October saw some sharp declines. MTSD average remained at +2 without increasing, but still positive. 2015: The market struggled most of the first part of the year and sold off hard in August: In just five days the DOW declined over 1,800 points. It recovered and ended the year down -398 points. MTSD average for the year was -1. 2016: The beginning of the year was weak and the DOW declined 1700 points from the first day of trading until February 10th. It then recovered and ended up +2,367 points for the year. MTSD average was a solid +2 at the end of the year and up +3 from the previous year’s close. 2017: The strong MTSD average from the close of 2016 fueled the market higher in 2017. The market started strong and finished strong… up +5,019 points on the year. MTSD average was the strongest reading we have in our database at +7 on the year. From the results of our study we concluded that the average MTSD per day reading is a reliable long-term indicator for the overall market. The updates are in the Long-Term Outlook section of the weekly Insights newsletter.


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Frequently Asked Questions We get a lot of questions regarding the terminology we use in our analysis of MT signals. We attempt to use common terms used in traditional stock market analysis when we write updates and newsletters, but we have necessarily had to create many new terms as well. We use three types of trends in our analysis: Long-term, intermediate-term and short-term. Those trends often contradict each other. It may be confusing when we talk about the weekly trend (UP) and that the long-term trend (DOWN) and the short-term T/S (next day) is DOWN, etc… The long-term trend is the big overriding trend that has the most powerful influence on market movements. This trend is highest trend and can take a market over at any time because it is the major trend. Typically, the long-tern trend will last 6-12 months or longer, possibly even years. Next in line of power and influence on the market is the intermediate-term trend which lasts from 2-7 days, but can last as long as a month or two in large moves. These trends are sometimes referred to as 'swing' moves. It's typically the 3-7 day 'counter-trend' we see often in the market but in larger moves in can last weeks or months. If the major trend is DOWN and we get a swing higher, it generally will not last more than 3-7 days after which the major trend will resume. BUT, and this is very important, the major trend can assert itself at any time because it is the most powerful trend in the market. What that means is that a promising looking swing move of 3-7 days may be cut short and the downtrend can re-assert itself suddenly and without notice. The larger time-frame has more influence on market movements than intermediate and short-term market movements aka shorter time frames. And so many of our clients do not pursue counter-trend (counter-trend meaning "against the MAJOR or higher time-frame trend") declines or rallies because of the shortness of the duration however there are clients who prefer a shorter time frame trade. These tend to be professional traders, prop traders or retail traders looking to capture swings of several days. The least influential or powerful trend is the short-term trend. Short-term trends occupy a very short time period that can last from a few minutes to hours to a day. These trends have the least power in the market and can also be the quickest to change direction. They are very difficult to trade, and you need to be extremely attentive and quick to capture these short-term movements.


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Innovation, Updates and Changes to Market Timer Market Timer is unique in that is looks at every facet of internal market data to glean information about the herding of financial market participants and supply/demand. Traditional chart-based technical analysis is centrally focused on price and indicators on price and/or volume which is lineal and lags real-time data. Market Timer’s focus is almost entirely on data which helps in identifying and visualizing herding of participants in the Balance of Power (BoP) and MT Volatility Index and MTSD in real-time because, as we’ve demonstrated with examples here, they have predictive value. We are also focused on measuring and quantifying supply/demand in the market using fundamental internal market data in our MT Supply/Demand Index (MTSD) – which despite massive computer power, no one else in the world has been able to measure. This is a very large area of study and our work has just begun. While we believe we have come to the end of the first major innovation cycle for Market Timer we are always looking for new correlations and ways to measure, quantify and track herding in the financial markets. The way in which we decide to make changes is entirely based on observation, testing and validation of the algorithms used in the quantitative analysis of Market Timer data and the success of our clients.

CONCLUSION Thank you for using Market Timer. The longer you study it, and use it, the more you’ll understand it and appreciate its unique power for timing the market. If you have any remaining questions please feel free to use our Client Portal support form. DISCLAIMER While Market Timer is the most accurate swing trading tool available, it cannot predict geopolitical risks and military conflicts around the world, outside of market hours, that would change the supply/demand and herding in the market.


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1Additional Resources Herding In Financial Markets "Some followers of the technical analysis school of investing see the herding behavior of investors as an example of extreme market sentiment.[8] The academic study of behavioral finance has identified herding in the collective irrationality of investors, particularly the work of Nobel laureates Vernon L. Smith, Amos Tversky, Daniel Kahneman, and Robert Shiller.[9][a] [emphasis added]. Hey and Morone (2004) analyzed a model of herd behavior in a market context. Their work is related to at least two important strands of literature. The first of these strands is that on herd behavior in a non-market context. The seminal references are Banerjee (1992) and Bikhchandani, Hirshleifer and Welch (1992), both of which showed that herd behavior may result from private information not publicly shared. More specifically, both of these papers showed that individuals, acting sequentially on the basis of private information and public knowledge about the behavior of others, may end up choosing the socially undesirable option. The second of the strands of literature motivating this paper is that of information aggregation in market contexts. A very early reference is the classic paper by Grossman and Stiglitz (1976) that showed that uninformed traders in a market context can become informed through the price in such a way that private information is aggregated correctly and efficiently. In this strand of the literature, the most commonly used empirical methodologies to test for herding toward the average, are the works of Christie and Huang (1995) and Chang, Cheng and Khorana (2000). Overall, it was shown that it is possible to observe herd-type behavior in a market context... this has important consequences for a whole range of real markets." [emphasis added] (SOURCE: https://en.wikipedia.org/wiki/Herd_behavior) --- "The herding measure essentially tests whether the observed distribution of Pit is fat tailed relative to the expected distribution under the null hypothesis that trading decisions are independent and conditional on the overall observed level of buying... (1) The latter term in this measure... accounts for the fact that we expect to observe more variation in the proportion of buys in stocks with few trades (see Lakonishok et al., 1992, for details). If small trades are independent, the herding measure will have a mean of zero. We calculate the mean herding measure in each month from January 1983 through December 2000 for both large and small trades. For small trades [$5000 or less], the mean herding measure is 7% and is positive in 214 out of 216 months. This measure of herding is in the same ballpark as the monthly herding measures of 6.8% to 12.8% estimated for individual investors by Barber, Odean, and Zhu (forthcoming). For large trades [$50,000 or more], the mean herding measure we estimate is 10% and is positive in 196 out of 216 months.[emphasis added]" (SOURCE: https://faculty.haas.berkeley.edu/odean/Papers%20current%20versions/DoRetailTradesMoveMarkets_RFS_2009.pdf?abstract_id=869827) --- "The term herd behavior as it applies to humans first appears in Dr. Wilfred Trotter's 1914 book Instincts of the Herd in Peace and War. It wasn't exactly a new idea, though Trotter can be credited with the phrase. Sigmund Freud, for instance, extensively discusses his ideas of crowd psychology, and Carl Jung suggests that such psychology is the result of universal or collective unconscious... ...You may see many examples of herd behavior in economics. For instance, if a few people begin to sell a certain type of stock, it may lead to a mass selling spree, panic, and leave the market open to crashing. [emphasis added] Similarly, you might look at the behavior in the retail environment on day after Thanksgiving sales (known as Black Friday). People have been injured in attempting to get to a special item offered at a very good price, when the doors of a store opens and the crowd stampedes in. Such stampedes have also occurred at rock concerts with open seating, where all people try to rush to get the closest seats to the front. Remember Tickle me Elmo or Beanie Babies, people were stealing, waiting in line and fighting over these items. These have occasionally had tragic results. Other areas that this plays in is Gangs, people join and belong to Gangs for a sense of being, belonging, safety in numbers, to have power, feel secure and safe in their area. Teenagers and school kids will smoke to be cool or accepted, they will join band or sports or some group that enable them to belong or to be with the same type of people, where they connect or feel safe. Look at sporting events where crowds of people yell and cheer for their teams, they get protective, where the same colors and dislike and opposite team. As the crowd cheers or boo's the fans join in and mod up. In riots, people get caught up in the violence and excitement and chaotic behavior and then that attitude continues to grow and progress and soon you have a stampede. One aspect of herd behavior that is often noted is that the herd is not completely


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interested in protection of the group. Instead self-interest (self-preservation) is a primary motivator. Herd animals, when they fear a predator, work to get into the center of the herd so they are less vulnerable and safer. Just as people have only self-interest in mind when they knock over others to get to a cheaply sold item, or the front seats of a rock concert; or even more so when they start selling or purchasing stocks to either make a profit or make an investment that will prove profitable in the very near future... ...Such things as housing prices can be determined by herd behavior and may be augmented by reports. In 2007, the Santa Rosa, California Press Democrat featured an angry letter to the editor asking them not to write anything else on the declines in the housing market. The writer was concerned that continued reports were driving the price of his own house down; in other words, he feared the herd instincts of others who would panic and try to sell before home prices dropped more, which would only lead to a drop in home prices and a flooded market. I say this a lot when I tell people that work with horses that when you try and prevent something from happening, you end up causing it to happen." (SOURCE: http://www.thinklikeahorse.org/index-33.html) --- Read more about herding in financial markets (Google search) REQUIRED CFTC DISCLAIMER

CFTC RULE 4.41 – HYPOTHETICAL OR SIMULATED PERFORMANCE RESULTS SUCH AS THOSE DESCRIBED HEREIN HAVE CERTAIN LIMITATIONS. UNLIKE AN ACTUAL PERFORMANCE RECORD, SIMULATED RESULTS DO NOT REPRESENT ACTUAL TRADING. ALSO, SINCE THE TRADES HAVE NOT BEEN EXECUTED, THE RESULTS MAY HAVE UNDER-OR-OVER COMPENSATED FOR THE IMPACT, IF ANY, OF CERTAIN MARKET FACTORS, SUCH AS LACK OF LIQUIDITY, SIMULATED TRADING PROGRAMS IN GENERAL ARE ALSO SUBJECT TO THE FACT THAT THEY ARE DESIGNED WITH THE BENEFIT OF HINDSIGHT. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFIT OR LOSSES SIMILAR TO THOSE SHOWN.

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