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| bio | website | |
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| location | ||
| age | ||
| visits | member for | 2 years, 3 months |
| seen | 16 hours ago | |
| stats | profile views | 76 |
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Feb 1 |
awarded | Yearling |
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Sep 25 |
awarded | Popular Question |
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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. |
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Aug 16 |
answered | Using rolling returns in a multivariate linear regression? |
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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). |
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Jun 28 |
awarded | Nice Answer |
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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 |
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Feb 6 |
awarded | Commentator |
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Feb 6 |
comment |
Calculating log returns using R lrets <- diff(log(prices)) |
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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. |
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Feb 2 |
awarded | Editor |
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Feb 2 |
revised |
Why does the minimum variance portfolio provide good returns? added 2 pertinent links and some more explanation |
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Feb 2 |
answered | Why does the minimum variance portfolio provide good returns? |
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Feb 2 |
awarded | Yearling |
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Jan 29 |
answered | Has spectrum analysis ever been used successfully to analyse historical price data? |
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Jan 29 |
comment |
Has spectrum analysis ever been used successfully to analyse historical price data? How is this useful as an answer? If you had any thoughts on applying Fourier transforms to financial data, outlining your thoughts would be more beneficial than to say you don't have time... just sayin... Financial econometric texts do have chapters devoted to spectral analysis btw. |
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Jan 29 |
answered | Are there ways to measure the risk aversion of a representative investor, based on publicly available market data? |
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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. |
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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. |
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Jan 29 |
answered | Which approach dominates? Mathematical modeling or data mining? |
