Below is a post i “borrowed” originally posted by hanover and the reason Im posting it here is because I think it offers excellent insight to some things hanover learned in 5 years of trading. I hope you get something out of it.
Put suitably calibrated Bollinger bands on a chart:
-
When the market is ranging, prices bounce between the upper and lower bands, and one profits by fading these bounces.
-
When the market is trending, prices stay in the appropriate (upper or lower) half of the bands, and if trending strongly enough, push the bands significantly outward. In this climate, one profits by riding the trends.
-
When the bands constrict, prices will eventually break out, pushing the band outward, and clinging to the band. Breakouts frequently offer explosive, �clean� price movement, at relatively low risk. But, exactly as you point out, there are plenty of false breakouts, and the breakout can peter out at any point.
The problem is that it�s no easier to forecast which of the three scenarios is imminent, than it is to simply forecast whether price will rise or fall.
All trading methods attempt to exploit one of these three scenarios, but very few are equipped to deal with more than one. One can try to combine (1) and (2), by trading in the direction of the next longer trend, but entering during a pullback. The assumption being that, in a ranging market, the pullback should be followed by a retracement to at least the mean, and in a trending market, the trend should continue. The BAT method attempts to accomplish this, albeit �in reverse�, by first entering on the assumption that a trend is establishing itself, and then hedging this somewhat by entering successive positions into a minor pullback.
Whatever the method, it doesn�t really matter what technical indicators one uses, because the bottom line is that one enters on a price bar, and exits on a price bar, and just about any indicator can be calibrated suitably to enter as early or as late, in an emerging price movement, as one wishes.
As general rules, every method involves an inversely proportional trade-off between the return-to-risk profile ® and the win rate (W):
Earlier entry into a price movement will attain greater profit if the trade succeeds (higher R), but will succeed less often (lower W); later, the reverse.
Setting a tighter protective stop will result in smaller losses (higher R), but will result in more frequent stopouts (lower W).
Exiting via targets locks in profit (higher W), and works better in ranging markets, but curtails profit (lowers R), if the price happens to trend.
A trailing stop works oppositely, i.e. well in trending markets, poorly in ranging. The tighter the stop, the greater the risk of being stopped out prematurely in a trend (lower R, higher W), but the less profit forfeited when the trend ultimately reverses. Moving one�s stop quickly to breakeven uses similar logic.
Trading concurrent positions results in smoother profit (higher overall W), as partial positions that get closed lock in profit, but curtails profit (lower R) on the closures; while all positions are subjected to the full weight of loss, if the protective stop is hit.
Trading without protective stops guarantees a 100% W, but potentially infinite risk (unlimited negative R). Not recommended.
And with regard to money management (MM), similar types of compromises apply:
Scaling into trades (�pyramiding�) escalates profits (return) if the market trends; but increases risk in like proportion, as losses will be greater if the hoped-for trend fails.
Averaging down into a position will increase profit in a ranging market, as prices bounce back, but leaves one open to proportionally greater loss if the bounce doesn�t occur, i.e. prices decide to trend adversely.
Increasing position size increases both risk and return in exactly direct proportion to each other.
There is no perfect �Holy Grail� method. The above compromises are implicit in all systems. To increase return, one has to increase risk of drawdown, in some way. The fact that so many diverse and conflicting approaches are recommended by successful traders suggests that price movement is very close to random in its nature. Put another way, trends do exist, but their occurrence is random, and likewise their length. To be consistently successful, then, a system must identify and exploit element(s) of non-randomness amongst the chaos.
�Non-randomness� might mean that, on balance, once a trend is established, it is more likely to continue than not; and/or that prices are more likely than not to reverse at extremes, points of prior S/R, pivots, or Fibos; and so on. Combinations, or confluences, of these factors can provide the necessary, albeit very small, edge. Statistical significance is important: 7 successes in 10 trials is fortuitous; 700 out of 1,000 is not.
Consequently, the only function of MM should be to preserve capital, allowing one�s account to survive a sequence of losses. MM has no bearing on expectancy, apart from magnifying its result.
Selection of timeframe likewise provides similar compromises.
Shorter means potentially, the following benefits:
More frequent opportunity to compound gains (and losses).
Greater, and accelerated, opportunity for positive expectancy (edge) to shine through (enhances return, mitigates risk).
Accelerates the learning curve (“feel” for the market, and what is likely or unlikely, to happen; experience in trade management).
Accelerated attainment of both statistical and psychological confidence.
Higher throughput = smoother, more consistent income (less jaggedness in equity curve). Crucial if trading is one�s sole/primary form of income, e.g. in a 5-trade losing sequence, a trader who makes 5 trades per day incurs negative income for a day; one trade per week incurs negative income for an entire month.
Less time to agonize over losses, and develop emotional attachment to individual trades.
Greater number of opportunities reduces temptation to (over)trade poorer setups.
But also the following very significant drawbacks:
Trading smaller movements greatly increases the significance of transaction costs (e.g. trading a 20 pip move with a 4 pip spread requires a 20% edge just to break even).
The shorter the timeframe, the greater the tendency for randomness in price movement (trends are shorter and more erratic).
Lifestyle implication: monitoring trades is both labor intensive and time-consuming.
All technical analysis makes the assumption that the elements of the past are, on balance, more likely to repeat themselves than not, in the imminent future. As such, TA is always a �lagging� process; all indicators tend to lag more so than price action.
Many traders underestimate the inherent costs. Beyond transaction costs (spread and rollover), there is the cost in allowing a margin for error in being unable to forecast swing highs and lows. One forfeits significant profit while allowing an emerging movement to confirm itself, ands also waiting for price to retreat to a trailing stop. It is arguably easier to forecast imminent price direction than the length of the move. But price must move far enough to overcome all of these costs. To state the obvious, the bottom line is that, if it moves far enough, and frequently enough, one profits; whenever it doesn�t, one loses.
Hopefully all of this illustrates some of the delicate balances involved, and that consistently profitable trading is extremely difficult. No matter how effective one�s method, or how disciplined one�s execution of it, frequent and/or prolonged drawdowns are inevitable.