Backtesting is just the procedure of using chronological records to experiment the act of some trading approach. Data Mining involves probing through data in order to establish patterns and find probable correlations between variables.

The Multiple Hypothesis Problem

Let’s presume that we backtest the approach against ten years of chronological marketplace data. The results are not very encouraging. Conversely, being violent and stumble traders as we are, we decide not to give up so easily. What about a ten day moving average? That might work out a little better, so let’s backtest it! We run another backtest and we find that the results still aren’t stellar, but they’re a bit better than the 20-day results. We decide to explore a little and run similar tests with 5-day and 30-day moving averages. Finally it occurs to us that we could actually just test every single moving average up to some point and see how they all perform. So we test the 2-day, 3-day, 4-day, and so on, all the way up to the 50-day moving average.

Now certainly some of these averages will perform poorly and others will perform fairly well, but there will have to be one of them which are the absolute best. For instance we may find that the 32-day moving average turned out to be the best performer during this particular ten year period. Does this mean that there is something special about the 32-day average and that we should be confident that it will perform well in the future? Unfortunately many traders assume this to be the case, and they just stop their analysis at this point, thinking that they’ve discovered something profound. They have fallen into the “Multiple Hypothesis Problem” pitfall.

Overfitting

Overfitting is a category of setback of the above problem. In overfitting we first look at the past and then build a single complex hypothesis that fits well with what happened.

Not likely, but we could always keep altering the model and taxing the approach in diverse samples (out of sample testing again) to see if our performance improves. When we stop getting performance improvements and the only thing that’s rising is the complexity of our model, then we know we’ve crossed the line into overfitting.

Conclusion

Data mining is a method to use our chronological price data to propose a feasible trading strategy, but that we have to be aware of the pitfalls of the multiple hypothesis problems and overfitting. The way to make sure that we don’t fall prey to these pitfalls is to backtest our strategy using a different dataset than the one we used during our data mining exploration. We commonly refer to this as “out of sample testing”.

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TA is based on using patterns that have formerly cropped to forecast the moves of the prospect no two patterns are ever accurately the same. How can they be when you list the variables that decide price action: trading methodologies, the number of contestants, the participants themselves, order sizes, market liquidity, and the list goes on. Technical analysis is self-fulfilling. If a price prototype emerges it is not as though every technical trader defines precisely the same entry point and pulls the prompt at exactly the same time or the market would not function. Price would jump instantly causing massive slippage and incomplete fills and then subside as traders took their profits. The opposite of this would of course be true if technical analysis was deemed as a poor method of analysis. With enough technical knowledge, a robust trading formula and practical pattern recognition you have a strong basis for a profitable edge. The fact that traders use different entry techniques, price patterns, technical indicators or no technical analysis whatsoever means that there is just enough self fulfilling prophecy present to give technical analysis profit potential.

Moving away from the idea of the self-fulfilling foretelling is the study of market psychology and herd mentality. Your skill to read this is an integral part of trading. Technical analysis is intended to give us a means to define this psychology and the consequential market action in the form of price or indicator patterns.

There is constantly a place for fundamental analysis in trading, even if this analysis is as essential as knowing when data will be released. In just the same way that technical traders react in a different way to the same price chart, fundamentalists will react differently to the same piece of news. Market reaction to fundamental news can be unpredictable and violent and the resultant price action will add another variable to the potential success of technical analysis.

Technical analysis can be used on all time frames. The universal consent is that the most significant price patterns and indicator set-ups are the ones that occur on the longer time frames, such as daily or weekly charts. It is the short-term price action that that paints the long-term picture and the long-term picture that has a determining effect on short-term moves.

We track their inferred activity by using a  group of short term moving averages. These are 3, 5, 8, 10, 12 and 15 day exponentially calculated moving averages. We select this combination because  three days is about half a trading week. Five days is one trading week. Eight days is about a week and a half.

The traders always lead the change in trend. Their buying pushes  prices up in anticipation of a trend change. The only way the trend can survive is if other buyers also come into the market. Strong trends are supported by long term investors. These are the true gamblers in the market because they tend to have a great deal of faith in their analysis. They just know they are right, and it takes a lot to convince them otherwise. When they buy a  stock they invest money, their emotions, their reputation and their ego. They simply do not like to admit to a mistake. This may sound overstated, but think for a moment about your investment in AMP or TLS. If purchased several years ago these are both losing investments yet they remain in many portfolios and perhaps in yours.

The investor takes more time to recognize the change in a trend. He follows the lead set by traders. We track the investors inferred activity by using a 30, 35, 40, 45, 50 and 60 day exponentially calculated moving average. Each average is increased by one week. We jump two weeks from 50 to 60 days in the final series because we originally used the 60 day average as a check point.

This reflects the original development of this indicator where our focus was on the way a moving average  crossover delivered information about agreement on value and price over multiple time frames. Over the years we have moved beyond this interpretation and application of the indicator. In the notes over the coming weeks we will show how this has developed.

Our starting point was the lag that existed between the time of a genuine trend break and the time that a moving average cross over entry signal was generated. Our focus was on the change from a  downtrend to an up trend. Our preferred early warning tool was the straight edge trend line which is simple to use and quite accurate. The problem with using a  single straight edge trend line was that some breakouts were false. The straight edge trend line provided no way to separate the false from the genuine.

On the other hand, the moving average crossover based on a 10 and 30 day calculation, provided a higher level of certainty that the trend break was genuine. However the disadvantage was that the crossover signal might come many days after the initial trend break signal. This time lag was further extended because the signal was based on end of day prices. We see the exact cross over today, and if we were courageous, we could enter tomorrow. Generally traders waited for another day to verify that the crossover had actually taken place which delayed the entry until 2 days after the actual crossover. This time lag meant that price had often moved up considerably by the time the trade was opened.

The standard solution called for a combination of short term moving averages to move the crossover point further back in time so that it was closer to the breakout signaled by a  close above the straight edge trend line. The drawback was that the shorter the moving average, the less reliable it became. In plotting multiple moving averages on a single chart display four significant features emerged. They were:

• A repeated pattern of compression and expansion in a group of six short term averages.
• The behavior was fractally repeated across different time frames. These short and long term groups were useful in understanding the inferred behavior of traders and investors.
• The degree of separation within groups and between groups provides a method of understanding the nature of the trend and trend change.
• The synchronicity was independent of the length of the individual moving averages. That is, at major trend turning points compression occurred across both long and short term groups and this provided early validation of signals generated by the straight edge trend line.

From these features there emerged this conclusion.

• The relationship between moving averages and price was better understood as a relationship between value and price. The crossover of two moving averages represented an agreement on value over two different time frames. In a continuous open auction which is the mechanism of the market, agreement on price and value was transient and temporary. Such agreement often preceded substantial changes in the direction of the trend. The GMMA became a tool for identifying the probability of trend development.

These broad relationships, and the more advanced relationships used with the GMMA are summarized in the chart. Over the following series of articles we will examine the identification and application of each of these relationships.

This is the most straightforward application of the GMMA and it worked well with “V’ shaped trend changes. It was not about taking the lag out of the moving average calculation. It is about validating a prior trend break signal by examining the relationship between price and value. Once the initial trend break signal is validated by the GMMA the trader is able to enter a breakout trade with a higher level of confidence.

The CBA chart shows the classic application of the GMMA. We start with the breakout above the straight edge trend line. The vertical line shows the decision point on the day of the breakout. We need to be sure that this breakout is for real and likely to continue upwards. After several months in a downtrend the initial breakout sometimes fails and develops as shown by the thick black line. This signals a change in the nature of the trend line from a resistance function prior to the breakout to a support function after the breakout.

The GMMA is used to assess the probability that the trend break shown by the straight edge trend line is genuine. We start by observing the activity of the short term group. This tells us how traders are thinking. In area A we see a compression of the averages. This suggests that traders have reached an agreement on price and value. The price of CBA has been driven so low that many traders now believe it is worth more than the current traded price. The only way they can take advantage of this ‘cheap’ price is to buy stock. Unfortunately many other short term traders have reached the same conclusion. They also  want to buy at this price. A bidding war erupts. Traders who believe they are missing out on the opportunity outbid their competitors to ensure they get a position in the stock at favorable prices.

The compression of these averages shows agreement about price and value. The expansion of the group shows that traders are excited about the future prospects of increased value even though prices are still rising. These traders buy in anticipation  of a trend change. They are probing for a trend change.

We use the straight edge trend line to signal an increased probability of a trend change. When this signal is generated we observe this change in direction and separation in the short term group of averages. We know traders believe this stock has a future. We want confirmation that the long term investors are also buying this confidence.

The long term group of averages, at the decision point, is showing signs of compression and the beginning of a change in direction. Notice how quickly the compression starts and the decisive change in direction. This is despite the longest average of 60 days which we would normally expect to lag well behind any trend change. This compression in the long term group is evidence of the synchronicity relationship that makes the GMMA so useful.

This compression and change in direction tells us that there is an increased probability that the change in  trend direction is for real – it is sustainable. This encourages us to buy the stock soon after the decision point shown.

The GMMA picks up a seismic shift in the markets sentiment as it happens, even though we are using  a 60 day moving average.. Later we will look at how this indicator is used to develop reliable advance signals of this change. This compression and eventual crossover within the long term group takes place in area B. The trend change is confirmed. The agreement amongst investors about price and value cannot last. Where there is agreement some people see opportunity. There are many investors who will have missed out on joining the trend change prior to area B. Now the change is confirmed they want to get part of the action. Generally investors move larger funds than traders. Their activity in the market has a larger impact.

The latecomers can only buy stock if they outbid their competitors.  The stronger the initial trend, the more pressure there is to get an early position. This increased bidding supports the trend. This is shown by the way the long term group continue to move up, and by the way the long term group of averages separates. The wider the spread the more powerful the underlying trend.

Even the traders retain faith in this tend change. The sell off that takes place in area C is not very strong. The group of short term averages dips towards the long term group and then bounces away quickly. The long term group of averages show that investors take this opportunity to buy stock at temporarily wakened prices. Although the long term group falters out at this point, the degree of separation remains relatively constant and this confirms the strength of the emerging trend.

The temporary collapse of the short term group comes after a 12% appreciation in price. Short term traders exit the trade taking short term profits at this level of return and this is reflected by the compression and collapse of the short term group of averages. As long term investors step into the market and buy CBA at these weakened prices, traders sense that the trend is well supported. Their activity takes off, and the short term group of averages rebounds, separates, and then run parallel to the long term group as the trend continues.

The GMMA identifies a significant change in the markets opinion about CBA. The compression of the short term and long term groups validates the trend break signal generated by a  close above the straight edge trend line. Using this basic application of the GMMA, the trader has the confidence necessary to buy CBA at, or just after the decision points shown on the chart extract.

Using this straightforward application of the GMMA also kept traders out of false breakouts. The straight edge trend line provides the first indication that a downtrend may be turning to an up trend. The CSL chart shows two examples of a false break from a straight edge trend line. We start with decision point A. The steep downtrend is clearly broken by a close above the trend line. If this is a  genuine trend break then we have the opportunity to get in early well before any moving average crossover signal.

This trend break collapses quickly. If we had first observed this chart near decision point B then we may have chosen to plot the second trend line as shown. This plot takes advantage of the information on the chart. We know the first break was false, and by taking this into account we set the second trend line plot. Can this trend break be relied upon? If we are right we get to ride a new up trend. If we are wrong we stand to lose money if we stay with a continuation of the downtrend. The straight edge trend line by itself does not provide enough information to make a good decision.

When we apply the GMMA we get a getter idea of the probability of the trend line break actually being the start of a new up trend. The key relationship is the level of separation in the long term group of averages, and trend direction they are traveling. At both decision point A and decision  point B the long term group is well separated. Investors do not like this stock. Every time there is a rise in prices they take advantage of this to sell. Their selling overwhelms the market and drives prices down so the downtrend continues.

The degree of separation between the two groups of moving averages also makes it more difficult for either of the rallies to successfully change the direction of the trend. The most likely outcome is a weak rally followed by a  collapse and continuation of the down trend. This observation keeps the trader, and the investor, out of CSL.

Looking forward we do see a convergence between the short term group of averages and the long term group of averages. Additionally the long term group begins to  narrow down, suggesting a developing level of agreement about price and value amongst investors in April and May. In late March the 10 day moving average closes above the 30 day moving  average, generating a classic moving average buy signal.

Using the GMMA we ignore this signal and the other GMMA convergence relationships. This decision is based on a more advanced understanding of the relationships revealed by the GMMA and we will examine these strategies in future articles.

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Paper Trading Values:

• Simulator fill prices are not real and won’t be attainable with real money
• There isn’t any financial risk in paper trading
• There is no emotion involved with paper trading

Two predominant problems of paper trading

• The trader does paper trading because they may not do with real money
• The trader views paper trading profitability

Profitability places the focus on currency instead of plan. The paper trader should not regard simple productivity as a sign of readiness to trade real money. Begin trading with real money when you are 60-70 percent proficient with your paper trades.

Paper trading is not only beneficial, but that paper trading is also necessary though the value received will be dependant upon the trader’s approach and attitude. Needless to say, paper trading as described is something that I have always strongly recommended.

‘Buyer perception’ varies among businessmen. It is the potential buyers do not buy the vehicle because they perceive a commodity as not unworthy it for them at the asking cost. Of course, they may think that the asking price is fair, but they didn’t like the color or the make. Yet, those prospective buyers may have bought the car anyway had the price been much lower. For those prospective buyers that did not buy, there may be a price that would turn them into buyers.

Presume you had ten potential car buyers out looking at the same car. At the present asking price, maybe only one of the ten feels it is worth buying at the asking price and would buy it. As you keep lowering the price, however, more and more may then consider it a good buy and want to buy it. Perception is a mental function. Therefore, we must address the ‘mental’, the ‘psychological’ angle of buying. When we consider the psychological aspect, we must consider the ‘emotional’ aspect as well. Our mental perception is mostly affected by information.

Working back from the actual buying and selling to the effects that may show the way to those final actions, you get a better accepting of the inner workings of market price action. The market trader can also reach a point of making highly accurate forecasts of market behavior, enough so as to be able to increase ones odds of getting on the right side of most trades.

Open trade is a fantastic opportunity for the smart trader who knows how to identify supply and demand. Most of the time, our entry is within seconds to minutes of the opening bell. Prices gap up because there are more buy orders at the open morning than there is available supply at the prior day’s closing price. They gap down because there are more sell orders at the open than willing demand at the prior day’s close. Therefore, market prices are almost always at price levels where there is a supply and demand imbalance at the open in the morning trade technique.

The input is to not stare at candles on your screen as red and green pictures and patterns. You must recognize what is happening behind the scenes in the morning trade. Whether you’re trading stocks, futures, options, or forex, the logic and rules never change. Again, the market imbalances are greatest at or near the open of trading in all markets. By the end of the first hour of trading each day, a large amount of novice trading capital is simply transferred into the accounts of the astute trader. If you can’t see the novice trader in markets, you most likely are the novice trader.

The dramatic price decline can only happen because there is much more supply at that level than willing demand. The dramatic rate of decline suggests a strong supply and demand imbalance at that level. Now, notice what happens the morning of the upgrade. Our job is to find this novice trader and simply take the other side of his or her trade and make the best of morning trade.

When you enter markets at price levels where supply and demand are out of balance in a big way, especially at or near the open of trading, moves in the market are typically very fast. This trade and the thoughts and rules that went with it are not meant to impress you. I mean to impress upon you the importance of looking at markets for what they really are which is simply an ongoing supply and demand equation. Opportunity exists when this simple and straightforward relationship is out of balance. Everything else in and around markets is just noise that is meant to invite you into markets at the wrong time and in the wrong direction.

Though there is some binding, we need to be at ease with each other. This terminology is evergreen all through this sector. Though there are vast variations in the approach, it is quite safe that most outsized financial institutions now employ both methods. Do remember that both have their own weaknesses and strengths.

The Trading Approach
A fundamental trader strongly believes that a share’s best performance is purely based on the fundamentals of the company like PE ratio, balance sheets, and profit/loss, ratios and business predictions. The technical trader believes that the future performance depends on simple information, namely the instrument price chart which encapsulates the company’s entire information.

A concept to be understood is that a technical trader will mainly be studying charts. Use fundamental analysis to define the business economy and therefore which industries offer the best growth future. This information is used to identify groups of target stocks. This finally uses technical analysis of the price charts to follow trends and select prospects.

Charts – Analysis and its components

Technical online trading is primarily about the study and analysis of charts. All charts are from share scope parcel. The various components of the chart are explained. The left and right hand side show the price of the share in pence. Along the bottom is the timescale. The chart itself has two colored bars, yellow and red called the candlesticks that represent the daily movement of the price of the share. It also shows the opening and closing price on the day. At the bottom of the chart is one of the most important pieces of information that you will use in your analysis, and this is volume. The numbers up the left and right hand side are the scale in millions, and indicate the number of shares traded on the market during the day. They are displayed as bars so that they are easy to read. You can instantly see where the volume is high, low or just average.