Capital Market Expectations Flashcards
Discuss the framework for developing capital market expectations.
- Specify the final set of expectations that are needed, including the time horizon to which they apply.
- Research the historical record.
- Specify the method(s) and/or model(s) that will be used and their information requirements.
- Determine the best sources of information needs.
- Interpret the current investment environment using the selected data and methods, applying experience and judgement.
- Provide the set of expectations that are needed, documenting conclusions.
- Monitor actual outcomes and compare them to expectations, providing feedback to improve the expectations-setting process.
What are the three qualities of a good forecast?
- unbiased, objective, and well researched
- efficient, minimizes the magnitude of forecast errors
- internaly consistent
Given n asset classes, quantify set of final expectations needed.
- n exepcted returns
- n standard deviations
- (n2 - n)/2 distinct correlations
What are the limitations of Economic Data?
- Time lag - The time lag in which economic data is collected, processes, and disseminated
- Revisions to the initial values
- Changes to the definition and/or calculation methonds.
- Indices of economic and financial data are periodically re-based, meaning the specific time period used as the base of the index is changed.
What are the three Data Measurement Errors and Biases?
- Transcript Errors
- Survirorship bias
- Appraisal (smoothed) data
What are transcription errors?
Errors in gathering and recording data.
What is Survivorship bias?
When data reflects only entities that have survived to the end of the period.
Contrast the results of appraisal (smoothed) data vs market-priced data and list the consequences of this difference.
Appraised values tend to be less volatile than market-determined valuese for the identical assets.
The consequences are:
- The calculated correlations with other assets tend to be smaller in absolute value than the true correlations
- The true standard deviation of the asset is baised downward.
What are the limitations of Histoircal data?
- Changes in regime
- Problems with long data series
- The risk that the data cover multiple regimes increases.
- Time series of the required length may not be available.
- In order to get data series of the required length, the temptation is to use high frequency data. However high frequency data is more sensitve to asynchronism across variables. As a result, high frequency data tend to produce lower correlation estimates.
How can ex post risk be a biased measure of ex ante risk?
Looking backward, we are likely to underestimate ex ante risk and overestimate ex ante anticipated returns. We need to evaluate whether asset prices in the period reflected the posibility of a very negative event that did not materialize during the period.
What are the biases in analysts’ methods and how can they be avoided?
- Data-mining bias
- Scrutinize the variable selection process for data-mining bias and be able to provide an economic rationale for the variable’s usefulness in a forecasting mode.
- Time-period bias
- Examine the forecasting relationship out of sample.
Describe the theoretical advantage of a shrikage estimate of covariance compared to a raw historical estimate.
The shrinkage estimate should be more accurate, given that the weights are chosen appropriately.
What are the psychological traps that can undermine an analyst’s ability to make accurate and unbiased forecasts?
- Anchoring trap
- Status quo trap
- Confirming evidence trap
- Overconfidence trap
- Prudence trap
- Recallibility trap
What is the anchoring trap and how would you mitigate it?
The anchoring trap is the tendency of the mind to give disproportionate weight to the first information it recieves on a topic. Try to address this trap by consciously attempting to avoid premature conclusions.
What is the status quo trap and how would you mitigate it?
The status quo trap is the tendency for forecast to perpetuate recent observations-that is, to predict no change from the recent past. This trap may be overcome with rational analysis used within a decision-making process.
What is the confirming evidence trap and how would you mitigate it?
The confirming evidence trap is the bias that leads individuals to give greater weight to information that supports an existing or preferred point of view than to evidence that contradicts it. Several steps can be taken to help ensure objectivity:
- Examine all evidence with equal rigor.
- Enlist an independen-minded person to argue against your preferred conclusion or decision.
- Be honest about your motives.
What is the overconfidence trap and how would you mitigate it?
The overcondifence trap is the tendency of individuals to overestimate the accuracy of their forecast. A good practice to prevent this trap is to widen the range of possibilities around the target forecast.
What is the prudence trap and how would you mitigate it?
The prudence trap is the tendency to temper forecast so that they do not appear extreme, or the tendency to be overly cautious in forecasting. A good practice to prevent this trap is to widen the range of possibilities around the target forecast.In addition, the most sensitive estimates affecting a forecast should ne carefully review in light of the supporting analysis.
What is the recallability trap and how would you mitigate it?
The recallability trap is the tendency of foecast to be overly influed by events that have left a strong impression on a person’s memory. To minimize the distortions fo the recallability trap, analysts shuold ground their conclusions on objective data and procedures rather than on personal memories and emotions.
What are the nine problems encountered in producing forecast?
- Limitation to economic data
- Data measurement error and bias
- Limitations of historical estimates
- The use of ex post risk and returns
- Non-repeating data patterns
- Failing to account for conditioning information
- Misinterpretation of correlations
- Physciological traps
- Model input and uncertainty
What are regime changes in historical data?
Shifts in the underlying fundametals.
What is the equation for the Gordon Growth Model? How do we use the model to find expected return?
What is the equation for the Grinold & Kroner model?
What is the equation for the expected return for bonds using the risk premium approach?
What is the equation for the ICAPM?
What is the equation for the correlation coefficient?
What is the equation for beta (ß)?
Using the correlation coefficient equation, what is the equation for beta (ß)?
What is the risk premium for asset i in a perfectly integrated market?