Confirmation bias: Humans are known to seek out data/evidence to confirm their current beliefs and to not seek out dis-confirming evidence of their biases.
This type of thinking can lead to believing in the likelihood of improbable events.
Example: being bearish on an asset (ticker, coin, etc..) that is continuously showing strength and has not shown signs of reversal yet, looking at lagging indicators like MACD and RSI to confirm your bias instead of price action.
Outcome bias: We judge the quality of a decision by whether its outcome was good or bad, not by whether the decision-making process was good or bad.
Example: *Following risk management (price targets, stop loss, etc.) and position sizing rules for account, but still ending up with losses --> potentially viewed as a BAD DECISION-MAKING PROCESS, which is false *NOT following ANY risk management rules or appropriate position sizing for account, but still ending up with a win --> potentially viewed as a GOOD DECISION-MAKING PROCESS, which is false.This is simply luck and gambling. Moral of the story is that good decision-making can still lead to bad outcomes.
Hindsight bias: "I knew it all along," creating narratives for events that happened in the past
Hindsight + outcome bias = overconfidence: I knew what to expect all along, it came out the way I expected so I am an expert. We feel more confident about making future decisions (trading) bc of past successes, but the confidence = based on an illusion
House Money Effect: When players, or in this case traders, are ahead in the game, they don't act like their winnings are 'real money.' Example: Putting your big profits from a previous play into a risky lotto, essentially seeing that money as "extra" or "separate" from your port and not properly following your risk management plan.
Break even Effect: People who had big losses and have an opportunity to break even will be extremely risk-seeking to get there. Example: Averaging down too much on an already losing trade and not following your position sizing rules.
Gambler's fallacy: On a losing streak, feel we're 'due' for a win, this is thinking based on luck and NOT the facts Example: Have lost 3 trades in a row, bound to win the next one
Prospect theory/loss-aversion theory: Traders/investors value gains and losses differently. Losses cause a greater emotional impact on an individual than does an equivalent amount of gain.
Example: Option
1) Being given $25 Option
2) Being given $50 and then having to give back $25
In both you are gaining the same amount at the end of each scenario, but because loss is involved with Option 2, traders will likely pick Option 1 as being more favorable.
This explains why we tend to be risk-seeking when all options are bad, exhibiting "nothing to lose" behavior because a sure loss = worse than a gamble since worst case scenario amount = not perceived as much worse than sure loss amount.
This type of thinking can lead to believing in the likelihood of improbable events.
Example: being bearish on an asset (ticker, coin, etc..) that is continuously showing strength and has not shown signs of reversal yet, looking at lagging indicators like MACD and RSI to confirm your bias instead of price action.
Outcome bias: We judge the quality of a decision by whether its outcome was good or bad, not by whether the decision-making process was good or bad.
Example: *Following risk management (price targets, stop loss, etc.) and position sizing rules for account, but still ending up with losses --> potentially viewed as a BAD DECISION-MAKING PROCESS, which is false *NOT following ANY risk management rules or appropriate position sizing for account, but still ending up with a win --> potentially viewed as a GOOD DECISION-MAKING PROCESS, which is false.This is simply luck and gambling. Moral of the story is that good decision-making can still lead to bad outcomes.
Hindsight bias: "I knew it all along," creating narratives for events that happened in the past
Hindsight + outcome bias = overconfidence: I knew what to expect all along, it came out the way I expected so I am an expert. We feel more confident about making future decisions (trading) bc of past successes, but the confidence = based on an illusion
House Money Effect: When players, or in this case traders, are ahead in the game, they don't act like their winnings are 'real money.' Example: Putting your big profits from a previous play into a risky lotto, essentially seeing that money as "extra" or "separate" from your port and not properly following your risk management plan.
Break even Effect: People who had big losses and have an opportunity to break even will be extremely risk-seeking to get there. Example: Averaging down too much on an already losing trade and not following your position sizing rules.
Gambler's fallacy: On a losing streak, feel we're 'due' for a win, this is thinking based on luck and NOT the facts Example: Have lost 3 trades in a row, bound to win the next one
Prospect theory/loss-aversion theory: Traders/investors value gains and losses differently. Losses cause a greater emotional impact on an individual than does an equivalent amount of gain.
Example: Option
1) Being given $25 Option
2) Being given $50 and then having to give back $25
In both you are gaining the same amount at the end of each scenario, but because loss is involved with Option 2, traders will likely pick Option 1 as being more favorable.
This explains why we tend to be risk-seeking when all options are bad, exhibiting "nothing to lose" behavior because a sure loss = worse than a gamble since worst case scenario amount = not perceived as much worse than sure loss amount.
Last edited: