About Market Timing

 About Market Timing

Historical patterns of trading are the foundation of market timing methods. When applied to historical data, every system you're likely to read about performs admirably. You would never learn of its failure in the past if it had worked. However, trends may and do shift, and what lies ahead is perpetually a mystery. Investors would have avoided a steep fall had a mechanism been put in place for the market trends of the 1970s, which encompassed a two-year severe bear market. In contrast, the extended bull market of the 1980s necessitated something else entirely. Additionally, conducting backtests in the 1970s with an ideal system that was developed in the 1980s would have yielded poor results. So far in the 1990s, investors have been more injured than helped by any defensive strategy.

It will be difficult to time the market if your mental stability is dependent on knowing where your money is at all times. No matter how much you try to comprehend market timing, its performance and direction will frequently elude you. Furthermore, they will disobey logic. The market's moves could appear understandable in the absence of timing. There are many analyses of every blip that appear in print, online, and on the media every single day. As a result of their persistence, economic and market patterns give the impression of being somewhat reasonable. When you start timing your investments, though, everything changes. No one can tell you how your timing models function unless you built them and know them inside and out, or unless you do the math yourself on a daily basis. Asking yourself to buy and sell based on faith is a common task. Given that the timing success is dependent on the interaction between your models and market patterns, the source of your short-term results may also remain a mystery. Your results may appear arbitrary when compared across years, quarters, and months.

The majority of us tend to believe that the current state of affairs will persist. But that isn't the case when it comes to market timing. Immediate previous performance will have little bearing on future performance. Therefore, you can never be sure of what's going to happen next. For the sake of this *timing simulator*, let's pretend that you have complete knowledge of the monthly returns of a successful approach over a 20-year timeframe. Naturally, a large portion of the monthly returns will reflect losses, but a considerable portion will reflect gains. Picture this: you make a deck of cards with all the returns written on it, put them in a hat, and then start drawing them at random. And picture yourself beginning with a stack of poker chips. Chips are awarded if a positive return is drawn. In this game, though, you'll have to surrender some chips to *the bank* if your return turns out to be negative. You can be reasonably certain if the first six cards you get are all positive. Plus, you'll hope that the fun moments won't end. Your joy may be short-lived, though, if you get a card that represents a loss out of the blue. And if you lose a lot of chips on the first card you draw, you could start to question if you still want to play this game. Even if you know the drawing is completely random, it's still possible to feel like you're on a *negative roll* and assume that the upcoming quarter will be just like the last if you get two bad cards in a row and see your chip pile diminish. However, you can't expect the next card to be predictable. All of this is readily apparent when one is merely engaged in a game of poker. Living the dream isn't easy. For instance, in the last quarter of 2002, our Nasdaq portfolio strategy—which aimed to beat the Nasdaq 100 Index—returned 5.9 percent, which was quite good for a portfolio that was solely invested in technology funds. However, the first quarter of 2003 saw a decline of 7.8 percent. At least among those who were aware of this method, the majority of investors persisted. However, they were greatly unsettled by the setback and the abrupt change in fortunes that they had anticipated. This same thing occurred, but in much larger numbers, with our more aggressive tactics. A number of investors were taken aback when they saw substantial first-quarter losses so soon after investing in such portfolios, which they had entered in the winter of 2002. Some people got out of the company because they thought the losses would keep piling up. If they had been more patient, they could have made double-digit gains in the rest of 2003, more than making up for their losses. Naturally, though, it was impossible to predict in advance.

Although most timers would deny it, every market timing technique has been *tuned* to work best in the past. What this implies is that they are based on data that has been hand-picked to ensure that they enter and exit the market at optimal moments. Consider it in light of this comparison. Let us pretend for a moment that we are attempting to construct, using data from the last 30 years, an improved version of the Standard & Poor's 500 Index. Looking back, it seems like we might easily boost the index's performance with some straightforward adjustments. It would be easy to *exclude* from the index, for example, the worst-performing stock industry and any companies that have declared bankruptcy during the last 30 years. By doing so, a significant amount of the *garbage* that has historically reduced performance could be eliminated. We could also quadruple the weightings of a handful of selected stocks in the new index—for example, Microsoft, Intel, and Dell—to inject a dose of positive return. A new *index* would be created, which has historically outperformed the actual S&P 500 in terms of return on investment. Perhaps we think we have found something really useful. The fact that this plan isn't likely to yield better results in the following three decades is obvious to anyone. By playing around with historical data in this straightforward way, you can easily create a *system* that passes the eye test. The term "data-mining" describes the process of sifting through large amounts of historical data in search of relevant pieces of information that can be "fitted" into a preconceived ideology or reality model. Any findings you derive from data-mining are useless and untrustworthy forecasts, according to academic researchers. One way or another, data-mining or optimization is the foundation of every market timing system. If you want to create a timing model, your only option is to look at previous periods and try to replicate their successes. Optimization is the foundation of every market timing model. One issue is that some systems, like as the improved S&P 500 example, are overly optimized and discard historical data in a manner that may not be dependable going forward. To illustrate the point, we lately examined a system that included some *rules* for when to send a purchase signal, and then we included a filter that said such a buy may only be sent out during four particular months annually. On paper, that technique appears fantastic since it eliminates the eight months of ineffective purchases. There isn't a foolproof method for telling which systems are over-optimized and which ones are resilient. Generally speaking, though, you should seek out simpler systems rather than more complex ones. It is more probable that an extremely complicated system will generate spectacular hypothetical returns than a simpler one. The less complicated system, on the other hand, is more likely to act in a predictable manner.

A long-term view and the capacity to dismiss short-term fluctuations as meaningless *noise* are crucial qualities in a successful investor. For those who want to buy and hold, this might be a rather simple task. However, you'll be entangled in the process of market timing and forced to concentrate on the short term as a result. It's not enough to just monitor short-term shifts; you'll also need to respond to them. Plus, you'll need to disregard them right away. If you ask me, there are occasions when that isn't easy. Smart people in the real world usually do one last *gut check* to see how they really feel before making a big decision. Nevertheless, this commonsense step must be eliminated and action must be taken when one is pursuing a mechanical method. This isn't always easy.

There will be extended stretches when your results are lower than or higher than the market average. Being in the market when prices are falling and out when prices are rising are both considered regular and expected activities, but your definition of normal and expected activity needs to be broader. On occasion, your earnings may fall short of money market fund rates. And if you're timing your short bets, you can end up broke while everyone else is flush with cash. Is that something you can roll with the punches as an investor? Avoid putting money into that plan if you can help it.

It is possible to get poor outcomes with even the best timing system. Although it may seem apparent, market timing introduces an additional degree of uncertainty to investing and presents yet another chance to be correct or incorrect. Applying your timing model to a fund that does not track the market would yield different results than what you would anticipate, even if your model consistently makes the right calls regarding the market. Use money that correspond well with your system for this purpose.

For me, the most important thing is that timing is really difficult. In my opinion, having someone else handle the actual timing moves is the way to go for most investors. Hiring an expert is an option for you. Another option is to delegate the trade-making to a trusted coworker, friend, or family member. In this approach, you can avoid letting your emotions interfere with your discipline. With your system in place, you can relax and enjoy your holiday. The most crucial thing is that you will no longer have to deal with the emotional challenges of entering and exiting the market.

No way!

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