Chapter 4

Forecasting with Mobility Oscillators

Mel Widner

The Mobility Oscillator, a technical indicator that measures how easily prices can move, is useful for assessing developing market conditions and anticipating price moves, even when conditions are relatively quiet.

CONGESTION AND MOBILITY

Does a market remember what it did previously? Each individual trader or investor in that market certainly remembers. Does the ensemble of traders and investors that make up a market have a collective memory? Can this be measured? Does this memory influence the future? Consider the following scenario and analysis, and judge for yourself.

If a trader enters or exits the market at a particular level, then that level becomes important to that trader, who will base future decisions on the entry or exit point. If the trader has entered the market and the market moves in either direction by some amount, the position may be closed for profit taking or as a stop loss. If the trader had exited the market previously, then he or she may reenter for similar reasons. The amount of the move and the time frame depend on the style and risk tolerance of the trader.

While a single action is not so important, the accumulation of actions for all traders in the market has significance. The composition of the market is varied. Some investors or fund managers may use fundamental analysis to determine entry and exit points based on assessed value. The fundamental levels are important as they can persist and, once evident, can reoccur and be reused in the future. There is also a cadre of traders and analysts who are watching the tape, trying to spot a trend, pattern, or an extreme or overdone condition. Trends and reversals are usually important for this group and they will jump on or off for a variety of reasons. These and other transactions cannot be hidden and are reflected in the price or index value.

If the price remains in a narrow range for a period of time, for whatever reason, then this price range becomes a region of congestion. There has been a balance of

buyers and sellers, and over time, their numbers accumulate. If the market moves far enough, then they may react creating a breakout. The losers will stop out and the winners will ride the trend. Other trend followers will jump on, and the process will continue until a new support or resistance level is tested.

From another viewpoint, the number of available buyers and sellers influences price changes. If initially there are about the same number of buyers and sellers and the price goes up, some additional new sellers, stimulated by the higher price, enter the market and the price is pushed back and equilibrates. Similarly if the price goes down, some additional buyers enter pushing the price back. For these supply-and-demand conditions, the reaction to a price move is stabilizing.

In some cases, the numbers of previously available buyers and sellers can be greater than the number of new buyers and sellers that can be stimulated by a move. As a result, the reaction to a price move is not always stabilizing. In fact, the opposite can occur. For example, if a move begins in a price range of high congestion and moves to a region of lesser congestion, then there can be fewer potential traders to counteract the move and the move can continue. This is destabilizing. If the move begins in a region of low congestion toward a region of higher congestion, there can be more traders to counteract and absorb the action. In this case, the reaction is overstabilizing.

Congestion may be viewed as a memory of the market that can influence future price movement. If price is moving about within a region of low congestion, there are few traders to counteract the moves and the price movement is considered mobile. Further, when prices move toward lower congestion, the move is likely to continue and the price is considered mobile. Conversely, when prices move either within high congestion or toward a region of higher congestion, then price is considered immobile. The ability or ease of a price to move is referred to as Mobility. That is not to say that price of high mobility will move, but that it is easier to do so.

External factors can change this scenario. Essentially anything that can cause significant numbers of new traders, who are not active, to enter the market will change the story. Changes in market conditions and departures from the previous history or expectations will do so. Earnings and growth potential, or lack thereof, are long-term drivers. News and unexpected events can lead to randomness or unpredictability. Other markets can influence a particular market indirectly. Sometimes these are factored in price, sometimes not. Divergence sometimes occurs and can lead to correction or equilibration.

Momentum is also an important factor. If a price move has sufficient inertia, then stopping it may take more than a region of congestion, or a support or resistance level. Not only are there traders sitting on the price level, there are those riding the trend. Therefore, momentum should be captured in the analysis process. This is possible by developing a historical record of congestion and price movement.

The premise to be explored is that price history contains a memory of previous events and that this will influence future events. So what is memory and how do you measure it? The most straightforward approach is to consider memory as simply a tally of that which has happened for some previous period. Pick a previous period and analyze the price action. One means of doing so is to calculate how prices are

distributed over the price range of that period. This distribution is called a Price Distribution Function (PDF). The PDF shows the amount of time that the price has spent within subdivisions of its price range for some previous period. If the amount of time spent is large, then there is congestion; and if the time spent is small, then there is a lack of congestion. An example of a PDF is shown in Figure 4.1 as a bar graph. High bars represent high congestion and low bars represent low congestion. The inverse relationship between congestion and mobility, as viewed by PDF analysis, is illustrated in Figure 4.1.

Distribution functions related to price are not by any means new. For example, the Black-Scholes model, a common tool for estimating the value of options and derivatives, utilizes a distribution of price changes to determine volatility. The data is assumed to fit a lognormal distribution, a standard distribution function form. Its volatility is derived, assuming this particular form, for subsequent evaluation. The analysis here is different. The PDF is a distribution over price, not price changes. It is simply a numerical distribution function computed by sorting data into bins. The shape is determined by the data history and can be virtually anything. There is no

Figure 4.1 Congestion and mobility. Congestion, as measured by a price Distribution Function (PDF), defines mobility, the PDF is

simply a tally of price action for a recent period. when current price is in a region of large congestion (the center of the bulge), then

mobility is small and movement is difficult. when current price is in a region of low congestion (the extreme left or right of the bulge), then mobility is large and movement easier. price movement from high congestion to low congestion is also easier.

HIGHER MOBILITY

LOWER MOBILITY

HIGHER MOBILITY

PRICERANGE