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Timing can make or break a business deal, especially when it comes to mergers and acquisitions. As entrepreneurs and business owners, you often find yourself grappling with the decision of when to make that crucial move. Let’s explore three key considerations that can help you navigate the intricate art of timing in the world of mergers and acquisitions. Venture capital-backed companies are not in the game for the long run. Their VCs would like to sell their portfolio after a few years and provide returns to the fund’s investors.…Continue reading….
Source: Inc
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Critics:
Whether market timing is ever a viable investment strategy is controversial. Some may consider market timing to be a form of gambling based on pure chance, because they do not believe in undervalued or overvalued markets. The efficient-market hypothesis claims that financial prices always exhibit random walk behavior and thus cannot be predicted with consistency.
Some consider market timing to be sensible in certain situations, such as an apparent bubble. However, because the economy is a complex system that contains many factors, even at times of significant market optimism or pessimism, it remains difficult, if not impossible, to predetermine the local maximum or minimum of future prices with any precision; a so-called bubble can last for many years before prices collapse.
Likewise, a crash can persist for extended periods; stocks that appear to be “cheap” at a glance, can often become much cheaper afterwards, before then either rebounding at some time in the future or heading toward bankruptcy. Proponents of market timing counter that market timing is just another name for trading. They argue that “attempting to predict future market price movements” is what all traders do, regardless of whether they trade individual stocks or collections of stocks, aka, mutual funds.
Thus if market timing is not a viable investment strategy, the proponents say, then neither is any of the trading on the various stock exchanges. Those who disagree with this view usually advocate a buy-and-hold strategy with periodic “re-balancing”. Others contend that predicting the next event that will affect the economy and stock prices is notoriously difficult.
For examples, consider the many unforeseeable, unpredictable, uncertain events between 1985 and 2013 that are shown in Figures 1 to 6 [pages 37 to 42] of Measuring Economic Policy Uncertainty.Few people in the world correctly predicted the timing and causes of the Great Recession during 2007–2009.
A 2004 study suggested that the best predictor of a fund’s consistent outperformance of the market was low expenses and low turnover, not pursuit of a value or contrarian strategy. Several independent organizations (e.g., Timer Digest and Hulbert Financial Digest) have tracked some market timers’ performance for over thirty years. These organizations have found that purported market timers in many cases do no better than chance, or even worse.
Institutional investors often use proprietary market-timing software developed internally that can be a trade secret. Some algorithms attempt to predict the future superiority of stocks versus bonds (or vice versa),[4][5] have been published in peer-reviewed journals.
Market timing often looks at moving averages such as 50- and 200-day moving averages (which are particularly popular). Some people believe that if the market has gone above the 50- or 200-day average that should be considered bullish, or below conversely bearish. Technical analysts consider it significant when one moving average crosses over another. The market timers then predict that the trend will, more likely than not, continue in the future.
Others say, “nobody knows” and that world economies and stock markets are of such complexity that market-timing strategies are unlikely to be more profitable than buy-and-hold strategies. Moving average strategies are simple to understand, and often claim to give good returns, but the results may be confused by hindsight and data mining.
A major stumbling block for many market timers is a phenomenon called “curve fitting“, which states that a given set of trading rules tends to be over-optimized to fit the particular dataset for which it has been back-tested. Unfortunately, if the trading rules are over-optimized they often fail to work on future data.
Market timers attempt to avoid these problems by looking for clusters of parameter values that work well or by using out-of-sample data, which ostensibly allows the market timer to see how the system works on unforeseen data.Critics, however, argue that once the strategy has been revised to reflect such data it is no longer “out-of-sample”.
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