Institutional / Smart Money Vs Retail Psychology + Rules
🎃 Many people approach technical analysis thinking that it is the first and most important thing to learn, which in reality should be the last. It is essential to first understand that trading psychology and risk management is the MOST IMPORTANT factor when trading within the market. Even if you have a strong technical analysis (which can never be perfect), you can still lose if you have poor risk management. You can lose even more if you are not patient enough and trade EMOTIONALLY.
🎃 The sad reality is that many professionals who have been trading for years still haven't realized this. I hope this little post will shed some light on advanced and novice traders. Every day I witness traders who make money and don't know why, or lose money and don't know why. One of the things I always like to advocate is that it is better to know why you lost a trade than not to know why you made money on a good trade. These are realistic expectations of the market, there is no simple magic spiral in technical analysis .
🧠 1.) Time frames: institutions (fund managers, funds, banks and whales) think in long time frames and monitor price action based on this (Years, Decades) small investors, retail traders monitor things in low time frames (Minutes, hours, days)
📜 Rule: always zoom out to higher time frame
🧠 2.) Objectivity: Small investors quickly switch between optimism and pessimism because of current price movements and news in the media. It can be a bull market one day and a bear market another day for a small investor. Institutional investors are not sentimental, they assess the growth rate of the market sector, the total market size available, the adoptation/acceptance, the growth of the network, the analysis of revenues (to predict profitability years and decades in advance). If an institutional investor reaches a conclusion, they hold it until the underlying financial situation changes.
📜 Rule: Follow the price not the news
🧠 3.) economic power: Small investors usually have limited money to invest, so they often resort to leverage, which typically results in full liquidity. Therefore small investors (who do not like to buy spot because it is not "cool") can easily be "thrown out" of trading because of the unlimited losses from leverage.
There is a reason why 90% of retail traders lose money.
Institutionalists brazenly exploit those with few resources and fear. Institutional investors have access to billions of dollars worth of resources and have teams of quantitative/statistical experts who control the automated trading algorithms.
📜 Rule: As long as you are not an expert, buy in Spot
🧠 4.) Influence: Institutional investors have deep pockets and can influence the general sentiment of the market through the press (news, social media and interviews). Institutional investors influence the news that small investors read. Institutionalists are well known for advertising higher prices for retailers to "buy at the top" to avoid FOMO (Fear of Missing Out). They are also notorious for creating tremendous market fear (FUD - Fear Uncertainty and Doubt), which encourages retailers to "sell at the bottom".
📜Rule: You pay the price for FUD & FOMO!!
🧠 5.) Behavior: Institutions actively participate in futures, options and derivatives markets. Both actively benefit from short-term price cycles as well as longer-term accumulation strategies. Small investors tend to think in short time horizons. They are sophisticated, financially strong and have expertise. Institutions make money by attracting retail investors into the market (via FOMO) and then liquidating their positions (via FUD). In the market, one person's loss is another person's gain.
📜 Rule: News is usually wrong!
👉Adoption stages
Many people misinterpret the exponential adoption process from a forward market perspective.
In short: You've probably heard the ingenious question that a scientist found that a lily started growing in a pond and doubled in size every day, then after 30 days covered 100% of the pond. Which day will it cover 50% of the lake?
The answer is on the 29th day, as it doubles in size every period. The lake goes from growing 50% to 100% when it doubles in size.
It is interesting to note that on day 28 the lake covered only 25% of the sample and on day 27 it covered 12.5%. It is therefore difficult to understand the exponential growth.
🎃 The sad reality is that many professionals who have been trading for years still haven't realized this. I hope this little post will shed some light on advanced and novice traders. Every day I witness traders who make money and don't know why, or lose money and don't know why. One of the things I always like to advocate is that it is better to know why you lost a trade than not to know why you made money on a good trade. These are realistic expectations of the market, there is no simple magic spiral in technical analysis .
🧠 1.) Time frames: institutions (fund managers, funds, banks and whales) think in long time frames and monitor price action based on this (Years, Decades) small investors, retail traders monitor things in low time frames (Minutes, hours, days)
📜 Rule: always zoom out to higher time frame
🧠 2.) Objectivity: Small investors quickly switch between optimism and pessimism because of current price movements and news in the media. It can be a bull market one day and a bear market another day for a small investor. Institutional investors are not sentimental, they assess the growth rate of the market sector, the total market size available, the adoptation/acceptance, the growth of the network, the analysis of revenues (to predict profitability years and decades in advance). If an institutional investor reaches a conclusion, they hold it until the underlying financial situation changes.
📜 Rule: Follow the price not the news
🧠 3.) economic power: Small investors usually have limited money to invest, so they often resort to leverage, which typically results in full liquidity. Therefore small investors (who do not like to buy spot because it is not "cool") can easily be "thrown out" of trading because of the unlimited losses from leverage.
There is a reason why 90% of retail traders lose money.
Institutionalists brazenly exploit those with few resources and fear. Institutional investors have access to billions of dollars worth of resources and have teams of quantitative/statistical experts who control the automated trading algorithms.
📜 Rule: As long as you are not an expert, buy in Spot
🧠 4.) Influence: Institutional investors have deep pockets and can influence the general sentiment of the market through the press (news, social media and interviews). Institutional investors influence the news that small investors read. Institutionalists are well known for advertising higher prices for retailers to "buy at the top" to avoid FOMO (Fear of Missing Out). They are also notorious for creating tremendous market fear (FUD - Fear Uncertainty and Doubt), which encourages retailers to "sell at the bottom".
📜Rule: You pay the price for FUD & FOMO!!
🧠 5.) Behavior: Institutions actively participate in futures, options and derivatives markets. Both actively benefit from short-term price cycles as well as longer-term accumulation strategies. Small investors tend to think in short time horizons. They are sophisticated, financially strong and have expertise. Institutions make money by attracting retail investors into the market (via FOMO) and then liquidating their positions (via FUD). In the market, one person's loss is another person's gain.
📜 Rule: News is usually wrong!
👉Adoption stages
Many people misinterpret the exponential adoption process from a forward market perspective.
In short: You've probably heard the ingenious question that a scientist found that a lily started growing in a pond and doubled in size every day, then after 30 days covered 100% of the pond. Which day will it cover 50% of the lake?
The answer is on the 29th day, as it doubles in size every period. The lake goes from growing 50% to 100% when it doubles in size.
It is interesting to note that on day 28 the lake covered only 25% of the sample and on day 27 it covered 12.5%. It is therefore difficult to understand the exponential growth.