behavioral Finance behavioral Finance attempts to understand and explain observed investor and Market behaviors, in other words behavioral Finance differs from traditional finance and then it focuses how investors in markets behave in practice rather than in theory.

Investors behave in a manner with outcomes that may appear irrational or suboptimal from a traditional Finance perspective.

Behavioral Finance is about understanding how people make decisions this may entail identifying a behavior and then modifying the behavior. So it more closely matches that assumed under the traditional Finance models resulting financial decisions. May produce an economic outcome closer to the optimal outcome of traditional Finance.

An investment said to have an 80% chance of success sounds far more attractive than one with a 20% chance of failure. The mind can't easily recognize that they are the same. This quote is from Daniel Kahneman, one of the founders of Behavioral economics suggested reading in this topic includes Thinking Fast and Slow by Kahneman or for a lighter read the undoing project by Michael Lewis.

People develop principles or beliefs based upon their experiences and they base their decision-making on those experiences alone heuristics simplified decision making but they lead to bias a systemic mistake these experiences or heuristics are imperfect and make people susceptible to error.

The first is representativeness. This is when an event is representative of a large population or sample an example of representativeness is assuming a good company is a good stock.

Second is overconfidence. This may be the most obvious Concept in behavioral Finance overconfident investors are often Diversified in thus more susceptible to volatility.

The third is anchoring. This is related to overconfidence. For example, you make your initial investment decision based on the information available to you at the time later. You get news that material effects any forecasts you initially made but rather than conduct new analysis, you simply revise your old analysis because you are anchored in the old thinking you revise the analysis won't fully reflect the new information.

The last is confirmation bias this leads to ignoring any info or evidence that contradicts person's views on an investment outcome. This can explain why the Bulls tend to remain bullish and the Bears tend to remain bearish regardless of what is happening in the market some examples of bias are overconfidence are 82% of people say they're in the top 30% of safe drivers when people say they're 90% sure of something they are usually only right 70% of the time and investors who trade more frequently have lower returns, even if we exclude trading costs in one study only those diagnosed with depression did not display overconfidence.

Here is an example of representativeness. Which of the following is more likely true about Linda most would select B, but B is simply a subset of a this example comes from research by diversity economy and the psychological review of October 1983.

Representativeness ties to the fact that people's actions are often based on stories rather than hard data. If enough people base their actions on the story rather than the data the story becomes a self-fulfilling prophecy and therefore a fact in itself. For example On July 28 1914 Austria-Hungary declared war on Serbia Panic ensued cash star of Europeans liquidated their us Holdings and there was an increase in shipping large quantities of gold from the US to Europe. These activities were driven by a narrative dating back to the 1907 Bankers Panic a financial crisis that saw the New York Stock Exchange Fall by almost 50% from its peak. The previous year nervous Europeans held this up as proof that America was unstable and that they should get their money out as fast as possible when in reality American stocks rallied during the war.

For more examples of how stories can help Drive economic events look for a book called narrative economics by Robert Schiller who won the Nobel Prize for economics in 2013.

Research by Terence Odin in 1999 analyzed trades from 10,000 clients at a certain discount brokerage firm. The study wanted to ascertain if frequent trading led to higher results over a one-year Horizon. The average return to purchase a security was 3.3% lower than the average return to a security sold. In other words, the more active the retail investor the less money they make this study was repeated numerous times in multiple markets in the results were always the same the authors concluded the Traders are basically paying fees to lose money.