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regime switching bias & halo effect

anyone know what is regime switching bias?

also does anyone have some examples for regime switching bias and halo effect? 

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I searched the curriculum for the term regime switching bias and found nothing.

are you talking about how there’s a risk of change in regime when trying to forecast values using historical data?

in the official cfa practice exams on behavioural finance one of the answer options offered the regime switching bias. i am also puzzled where they get it from because i read all the official books, and i have not seen them actually explain what it is. 

2.2.3. The Limitations of Historical Estimates

L3V3R14-80 With justification, analysts frequently look to history for information in developing capital market forecasts. But although history is usually a guide to what we may expect in the future, the past cannot be simply extrapolated to produce future results uncritically. A historical estimate should be considered a starting point for analysis. The analysis should include a discussion of what may be different from past average results going forward. If we do not see any such differences, we may want to project the historical estimates into the future (perhaps after making certain technical adjustments). However, making such projections without raising the question of differences is questionable. Changes in the technological, political, legal, and regulatory environments, as well as disruptions such as wars and other calamities, can alter risk–return relationships. Such shifts are known as changes in regime (the governing set of relationships) and give rise to the statistical problem of nonstationarity (meaning, informally, that different parts of a data series reflect different underlying statistical properties). For example, the shifts in US central bank policy in 1980 began a period of declining and subsequently stable inflation that is widely recognized as representing a break with the past. Also, disruptive events in a particular time period may boost volatilities in a manner that is simply not relevant for the future. However, extending a dataset to the distant past increases the chance of including irrelevant data. The well-informed analyst tracks the range of events that can indicate an important change in a time series. Statistical tools are available to help identify such changes or turning points

(Institute 16)

CFA Program Level III Volume 3 Applications of Economic Analysis and Asset Allocation. CFA Institute,

CP

useful.. thank you.

cpk123 wrote:
2.2.3. The Limitations of Historical Estimates

L3V3R14-80 With justification, analysts frequently look to history for information in developing capital market forecasts. But although history is usually a guide to what we may expect in the future, the past cannot be simply extrapolated to produce future results uncritically. A historical estimate should be considered a starting point for analysis. The analysis should include a discussion of what may be different from past average results going forward. If we do not see any such differences, we may want to project the historical estimates into the future (perhaps after making certain technical adjustments). However, making such projections without raising the question of differences is questionable. Changes in the technological, political, legal, and regulatory environments, as well as disruptions such as wars and other calamities, can alter risk–return relationships. Such shifts are known as changes in regime (the governing set of relationships) and give rise to the statistical problem of nonstationarity (meaning, informally, that different parts of a data series reflect different underlying statistical properties). For example, the shifts in US central bank policy in 1980 began a period of declining and subsequently stable inflation that is widely recognized as representing a break with the past. Also, disruptive events in a particular time period may boost volatilities in a manner that is simply not relevant for the future. However, extending a dataset to the distant past increases the chance of including irrelevant data. The well-informed analyst tracks the range of events that can indicate an important change in a time series. Statistical tools are available to help identify such changes or turning points

(Institute 16)

CFA Program Level III Volume 3 Applications of Economic Analysis and Asset Allocation. CFA Institute,

So … let me get this straight:

You can learn the answers to CFA questions by … reading the curriculum?

Whoda thunk it?

Simplify the complicated side; don't complify the simplicated side.

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