Especulador96
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Influential educators often spread erroneous ideas that end up costing the community money. One of the most harmful opinions, sadly accepted by most investors, is that all timeframes are equal for practical purposes, since the market is fractal. With this article, I aim to shed light on this phenomenon and demonstrate that timeframes are more than just a matter of preference.
Mass Psychology and Historical Record
Shorter timeframes, such as intraday charts, offer a price record and a more limited context compared to longer timeframes—daily, weekly, or monthly—which can make it difficult to identify clear and reliable patterns. Additionally, another relevant aspect is that the duration of a market phenomenon is often an indicator of its consistency: trends that persist over time tend to reflect more stable and predictable behavior.
For this reason, investors prefer to base their decisions on an analysis that considers a greater amount of historical data, such as that provided by longer timeframes. The lack of a complete history limits the ability to detect solid and consistent patterns, increasing the risk of less informed decisions.
News, Events, and Rumors
The appearance of a surprise announcement about interest rates or a geopolitical event can trigger panic or euphoria among investors, leading them to buy or sell assets without a clear strategy. Even a simple rumor can cause chaos in price charts, highlighting how unpredictable humans are in the face of new circumstances. This instability is generally clearly reflected in 5-, 15-, or 60-minute charts, where volatility increases dramatically. The historical record of this irrationality rarely affects trends in longer timeframes, which offer a more stable and consistent perspective.
On this, the renowned investor and author, Dirk du Toit, has said the following:
"The smaller your timeframe, the greater the randomness of what you're observing. If you're watching price changes every five or fifteen minutes, the degree of randomness is very high, and your probability of anticipating the next correct price movement, or series of price movements, is very low."
Manipulation:
Higher timeframes require a greater volume of money to be manipulated, as the interests that form the price action have matured over a longer period (increasing their reliability). Generally, higher timeframes are operated by more capitalized participants who trade with long-term objectives.
High-frequency trading (HFT) is a form of automated trading that uses advanced algorithms, high-speed computer systems, and low-latency connections to execute a large number of trades in fractions of a second. This type of trading is characterized by exploiting small market inefficiencies, operating with large volumes, and holding positions open for extremely short periods.
In lower timeframes, price movements can appear random or "noisy" due to HFT activity, which makes traditional technical analysis difficult for manual traders.Technical patterns (such as supports, resistances, or breakouts) can break quickly due to algorithmic action, which does not operate based on classical patterns, but on high-frequency data like order flow or statistical correlations.
Randomness increases with shorter timeframes. An example of this is the reduction in the success rate of trading systems as we move to lower timeframes. Profitable systems (documented) on daily charts can become unusable on timeframes like 4-hour or 1-hour.
Additional Ideas:
-All classic indicators (MACD, RSI, Bollinger Bands, Keltner Channels, Donchian Channels, Williams Alligator, Ichimoku Cloud, Parabolic SAR, DMI, etc.) have been created based on timeframes higher than intraday.
-All known classic methodologies (Dow Theory, Chartism, Elliott Theory, Harmonic Patterns, Wyckoff Method, Gann Theories, Hurst Cycles, Japanese Candlestick Patterns, etc.) were created with a focus on timeframes higher than intraday.
-All great classic analysts, and most great current investors, apply an investment approach higher than the intraday timeframe.
On Some Authors:
-Richard W. Schabacker in his book “Technical Analysis and Stock Market Profits” (1932) structured market fluctuations into Major Movements (monthly chart or higher), Intermediate Movements (weekly chart), and Minor Movements (daily chart). His analyses were based on the study of these timeframes.
"The more time it takes for the chart to form the image of any formation, the greater the predictive significance of that pattern and the longer the subsequent movement, the length, size, and strength of our formation."
-Dirk du Toit in his book titled “Bird Watching in Lion Country” comments:
"The smaller your timeframe, the greater the randomness of what you're observing. If you're watching price changes every five or fifteen minutes, the degree of randomness is very high, and your probability of anticipating the next correct price movement, or series of price movements, is very low."
"A coin, just like a five-minute chart, has no memory. Just because it has come up heads eight times in a row, it doesn't start to 'adjust' to provide the required probability balance of a 50/50 ratio in a given number of tosses. Five- or fifteen-minute charts are the same. Trying to predict whether the next five-minute period will end up or down is exactly like flipping a coin."
Conclusions:
I do not intend to dismiss methodologies that take advantage of fluctuations in shorter timeframes. My goal is to warn retail investors about the risks of intraday trading: randomness, manipulation, and limited information turn these timeframes into dangerous terrain. Even effective systems proven on daily charts tend to suffer statistical wear. In contrast, higher timeframes offer clarity and consistency, backed by mass psychology, historical record, and trading volume.
Mass Psychology and Historical Record
Shorter timeframes, such as intraday charts, offer a price record and a more limited context compared to longer timeframes—daily, weekly, or monthly—which can make it difficult to identify clear and reliable patterns. Additionally, another relevant aspect is that the duration of a market phenomenon is often an indicator of its consistency: trends that persist over time tend to reflect more stable and predictable behavior.
For this reason, investors prefer to base their decisions on an analysis that considers a greater amount of historical data, such as that provided by longer timeframes. The lack of a complete history limits the ability to detect solid and consistent patterns, increasing the risk of less informed decisions.
News, Events, and Rumors
The appearance of a surprise announcement about interest rates or a geopolitical event can trigger panic or euphoria among investors, leading them to buy or sell assets without a clear strategy. Even a simple rumor can cause chaos in price charts, highlighting how unpredictable humans are in the face of new circumstances. This instability is generally clearly reflected in 5-, 15-, or 60-minute charts, where volatility increases dramatically. The historical record of this irrationality rarely affects trends in longer timeframes, which offer a more stable and consistent perspective.
On this, the renowned investor and author, Dirk du Toit, has said the following:
"The smaller your timeframe, the greater the randomness of what you're observing. If you're watching price changes every five or fifteen minutes, the degree of randomness is very high, and your probability of anticipating the next correct price movement, or series of price movements, is very low."
Manipulation:
Higher timeframes require a greater volume of money to be manipulated, as the interests that form the price action have matured over a longer period (increasing their reliability). Generally, higher timeframes are operated by more capitalized participants who trade with long-term objectives.
High-frequency trading (HFT) is a form of automated trading that uses advanced algorithms, high-speed computer systems, and low-latency connections to execute a large number of trades in fractions of a second. This type of trading is characterized by exploiting small market inefficiencies, operating with large volumes, and holding positions open for extremely short periods.
In lower timeframes, price movements can appear random or "noisy" due to HFT activity, which makes traditional technical analysis difficult for manual traders.Technical patterns (such as supports, resistances, or breakouts) can break quickly due to algorithmic action, which does not operate based on classical patterns, but on high-frequency data like order flow or statistical correlations.
Randomness increases with shorter timeframes. An example of this is the reduction in the success rate of trading systems as we move to lower timeframes. Profitable systems (documented) on daily charts can become unusable on timeframes like 4-hour or 1-hour.
Additional Ideas:
-All classic indicators (MACD, RSI, Bollinger Bands, Keltner Channels, Donchian Channels, Williams Alligator, Ichimoku Cloud, Parabolic SAR, DMI, etc.) have been created based on timeframes higher than intraday.
-All known classic methodologies (Dow Theory, Chartism, Elliott Theory, Harmonic Patterns, Wyckoff Method, Gann Theories, Hurst Cycles, Japanese Candlestick Patterns, etc.) were created with a focus on timeframes higher than intraday.
-All great classic analysts, and most great current investors, apply an investment approach higher than the intraday timeframe.
On Some Authors:
-Richard W. Schabacker in his book “Technical Analysis and Stock Market Profits” (1932) structured market fluctuations into Major Movements (monthly chart or higher), Intermediate Movements (weekly chart), and Minor Movements (daily chart). His analyses were based on the study of these timeframes.
"The more time it takes for the chart to form the image of any formation, the greater the predictive significance of that pattern and the longer the subsequent movement, the length, size, and strength of our formation."
-Dirk du Toit in his book titled “Bird Watching in Lion Country” comments:
"The smaller your timeframe, the greater the randomness of what you're observing. If you're watching price changes every five or fifteen minutes, the degree of randomness is very high, and your probability of anticipating the next correct price movement, or series of price movements, is very low."
"A coin, just like a five-minute chart, has no memory. Just because it has come up heads eight times in a row, it doesn't start to 'adjust' to provide the required probability balance of a 50/50 ratio in a given number of tosses. Five- or fifteen-minute charts are the same. Trying to predict whether the next five-minute period will end up or down is exactly like flipping a coin."
Conclusions:
I do not intend to dismiss methodologies that take advantage of fluctuations in shorter timeframes. My goal is to warn retail investors about the risks of intraday trading: randomness, manipulation, and limited information turn these timeframes into dangerous terrain. Even effective systems proven on daily charts tend to suffer statistical wear. In contrast, higher timeframes offer clarity and consistency, backed by mass psychology, historical record, and trading volume.
