The idea of market expectations, for me, is a statistical one that helps keep me grounded. If you track any of the market outlooks I provide, it's important (and easy) to understand what that means. To whatever extent it can also help you remain grounded when completing your analysis or making trading decisions, all the better.
Consider a baseball pitcher who throws 10 fast balls in a row, averaging 95 miles per hour for those pitches. On pitch 11, a spectator expects to see another fast ball around 95 miles per hour. It may be more or less, but it would be unusual to now witness a 115 mile per hour pitch or a 75 mile per hour one. Although the sample set was small, using a straightforward example seems better suited to a trading approach that is part art and part science.
In technical analysis, a linear regression channel provides a nice example of expectations. The channel is created by drawing a line of best fit for the data (i.e., the daily close for a stock). When the trend is intact, we expect future closes to be near that regression line. In addition to a central regression line, there are upper and lower channel lines constructed from extreme movement for the data period.
When using a regression channel for trading, we also expect price movement to go from one regression line to another with each serving as support or resistance along the way. Momentum and volume can be monitored as price moves towards or away from each of these three lines. When price fails to reach a line or breaks strongly away from it, we make somewhat subjective assessments about price (weak/strong). Collectively these assessments help us make trade decisions and forecasts about future prices.
The Weight of the Evidence
I heard Martin Pring use this expression when discussing a market forecast and it really resonated with me. Typically only extremely strong bull moves and extremely strong bear moves are accompanied by respectively strong bullish and bearish readings for all of the indicators you use. The market movements that fall between those two extremes require a more thorough assessment of:
- Indicators that are confirming the move
- Indicators that are diverging from the move and
- The importance of each in the current environment.
Traders can qualitatively assess these when making trading decisions or they may use a more rigorous quantitative approach with a model that assigns specific values to indicator readings (i.e. an oversold oscillator may be assigned the value +1). The model then signals a bullish or bearish phase depending upon the sum of the different indicator values in the model.
If you're not completely system and quant-oriented, still consider some tally of bullish and bearish indications to help you decide where the weight of the evidence lies. As with all trading decisions, it doesn't have to be all or nothing. You may decide to establish partial hedges in a neutral zone, full hedges when conditions are counter to your existing positions and no hedge when your positions are consistent with the market "weight of the evidence" you review.
The Black Swan
Regardless of how effectively different systems work in the past, there are no guarantees going forward. Clearly the 2008 markets provided traders with proof of this. An added difficulty for extending statistical logic to the stock market is that market returns follow a normal curve pattern, but not a nice symmetrical textbook example of one. Extreme positive and negative returns occur more often with the stock market than a typical normal curve distribution (aka "fat-tails").
Nassim Taleb describes the difficulties that arise when we expect the market to adhere to model behavior in two books, "Fooled by Randomness" and "The Black Swan." A bottom line observation from these books is that even though you may have never seen a black swan, it's not proof they don't exist. Last fall when the CBOE Volatility Index (VIX) surpassed previous all-time highs, it would have been costly to use that as a guarantee that prices would re-bound as the VIX retraced.
Putting it Together
Hopefully there aren't too many disjointed thoughts here. It seemed reasonable to tie them together a bit.
Quantitative analysis and trading in the form of indicators, models, systems, etc. is a valid approach to the market that can certainly be more qualitatively applied by discretionary traders. Consider what you expect to happen given past movement in an index or security, identify arguments for and against these expectations, and respond accordingly. Regardless, always know that the unexpected can occur and be prepared in advance by using good money management and risk management practices. Consider the black swan that could really have a negative impact on your trading.
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Clare White
Contributing Writer and Options Strategist
Optionetics.com ~ Your Options Education Site
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