{"id":112,"date":"2019-12-13T00:25:07","date_gmt":"2019-12-13T00:25:07","guid":{"rendered":"https:\/\/straussresearch.com\/?page_id=112"},"modified":"2020-01-18T04:24:18","modified_gmt":"2020-01-18T04:24:18","slug":"a-rule-based-approach","status":"publish","type":"page","link":"https:\/\/straussresearch.com\/index.php\/a-rule-based-approach\/","title":{"rendered":"A Rule-Based Approach instead of Statistics"},"content":{"rendered":"\t\t
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Having spent a lot of time studying how to combine fundamental and technical analysis in the investment process, one of my conclusions is that <\/strong>much of the value from using technical analysis is not from looking at any one chart by itself.\u00a0 It is from studying multiple charts, and analyzing the relationships among them<\/span>.\u00a0 <\/strong><\/p>

Analyzing market relationships can <\/strong>help us find information that has not been arbitraged away.\u00a0 However, rather than analyzing such market relationships with statistical methods such as regressions and correlations<\/span>, it is often more effective to put together the pieces of the puzzle by studying multiple charts and using a rule-based approach<\/span>.<\/strong><\/p>

An example is seen in the relationship between the S&P 500 and technology stock Nvidia (NVDA) in the late 2015 – early 2016 period.\u00a0 The S&P 500 started to show signs of weakness in December 2015 and then experienced a sharp correction in the first quarter of 2016.<\/strong><\/p>

Technology stock Nvidia (NVDA) had broken out to a new high in October 2015, and made a strong advance for two months.\u00a0 It was consolidating to its 50-day moving average in late December 2015 (see chart below).\u00a0 The stock had good fundamentals as well as good relative strength and good money flow, characteristics that normally occur at the start of a powerful move up.<\/strong><\/p>

Figure 6\u00a0 \u00a0Nvidia (NVDA) — late 2015 thru early 2016<\/strong><\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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In a normal m<\/strong>arket environment, this pullback to the 50-day moving average would have been a perfect time to buy NVDA.\u00a0 But <\/strong>in January 2016, the stock was dragged down by the correction in the overall market.\u00a0 <\/strong><\/p>

This market correction provided a good opportunity to buy NVDA.\u00a0 As seen in the chart, when as the correction ended in February 2016, NVDA quickly recovered, and soon moved sharply higher.<\/strong><\/p>

Therefore, it would be useful to have an investment rule stating “When the overall market goes into a correction, look for buying opportunities in stocks that had recently broken out to new highs and made powerful moves up — but then were dragged down by the correction.”<\/strong><\/p>

(Note:\u00a0 this situation <\/strong>is discussed in more detail in the article entitled “Short-term Market Analysis”<\/a> in the \u201cExcerpts from White Papers\u201d section.)<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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…\u00a0 Statistical calculations do a good job of summarizing the relationship between two assets over a given time period, such as the past 12 months<\/span>.<\/strong><\/p>

However, these calculations do not consider current market conditions, such as whether the market is overbought, oversold, in a correction, etc.\u00a0<\/strong><\/p>

In many cases, what is important for an investment decision is not a summary of the relationship over some time period such as the past 12 months<\/span>.<\/strong><\/p>

Instead, what matters is the current technical condition of the market, relative to the current technical position of <\/span><\/strong>the stock<\/span>.<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Because the overall market and the sector have a lot of influence on the behavior of a stock, the analysis should be done in a top-down manner, starting with the condition of the overall market, then sectors and industry groups, and finally individual stocks.\u00a0 Then we can put together the pieces of the puzzle with logical decision-making rules, rather than statistical methods<\/span>.<\/strong><\/p>

Based on numerous case studies, I have developed a set of decision-making rules for various market conditions.\u00a0 These are <\/span><\/strong>compiled in a \u201cplaybook\u201d for market strategy<\/span>.\u00a0 This covers a variety of different market conditions, such as:<\/strong><\/p>