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Feb
27
awarded  Notable Question
Feb
1
awarded  Yearling
Sep
25
awarded  Popular Question
Sep
11
comment Is there any research on applying state-space or dynamic linear models to forecasting equity risk premia?
Is this about dynamic regression of single security returns on risk factors (market, value, size, momentum, . .)? I see that as a 2-step process, first estimating betas for each security for each risk factor under consideration. Second; forecast expected returns to each risk factor and then use those forecasts coupled with betas to forecast expected returns to the security.
Aug
16
answered Using rolling returns in a multivariate linear regression?
Jul
25
comment Choice of prior as a shrinkage target in portfolio construction?
You can think of some weight vector as a shrinkage target, which also corresponds to some properties of the covariance matrix. Jagannathan & Wang's paper on the implication of no-short-sale constraint helps get it, i.e. a constraint of non-negative weights has an equivalence in shrinking to covariance matrix (toward some prior).
Jun
28
awarded  Nice Answer
Mar
29
revised Are there ways to measure the risk aversion of a representative investor, based on publicly available market data?
deleted 80 characters in body
Feb
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awarded  Commentator
Feb
6
comment Calculating log returns using R
lrets <- diff(log(prices))
Feb
3
comment Choice of prior as a shrinkage target in portfolio construction?
in continuing +Patrick Burns question, how would you use a 'minimum risk' portfolio as a shrinkage target? I see the global minimum variance as natural, but aren't you contradicting yourself by saying that the minimum risk portfolio is a candidate shrinkage target with the advantage of not needing return estimates. I see, three possibilities 1] global min. variance portfolio 2] equal weighted portfolio 3] market portfolio as shrinkage targets. I don't get how the portfolios along the 'frontiers' are each a shrinkage target.
Feb
2
awarded  Editor
Feb
2
revised Why does the minimum variance portfolio provide good returns?
added 2 pertinent links and some more explanation
Feb
2
answered Why does the minimum variance portfolio provide good returns?
Feb
2
awarded  Yearling
Jan
29
answered Has spectrum analysis ever been used successfully to analyse historical price data?
Jan
29
answered Are there ways to measure the risk aversion of a representative investor, based on publicly available market data?
Jan
29
comment Are there ways to measure the risk aversion of a representative investor, based on publicly available market data?
More precisely he wrote: Modern markets show considerable micro-efficiency (for the reason that the minority who spot aberrations from micro efficiency can make money from those occurrences and, in doing so, they tend to wipe out any persistent inefficiencies). In no contradiction to the previous sentence, I had hypothesized considerable macro inefficiency, in the sense of long waves in the time series of aggregate indexes of security prices below and above various definitions of fundamental values.
Jan
29
comment Are there ways to measure the risk aversion of a representative investor, based on publicly available market data?
@Dimitris, because you cite Samuelson's paper, there is also something else that Samuelson spoke of. He offered the dictum that the stock market is ‘‘micro efficient’’ but ‘‘macro inefficient.’’ That is, the efficient markets hypothesis works much better for individual stocks than it does for the aggregate stock market.
Jan
29
answered Which approach dominates? Mathematical modeling or data mining?