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| bio | website | |
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| location | ||
| age | ||
| visits | member for | 1 year |
| seen | 1 hour ago | |
| stats | profile views | 152 |
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Oct 2 |
awarded | Enthusiast |
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Sep 28 |
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What is the instantaneous P&L of a Variance Swap? Perhaps he means something like the instantaneous credit risk of a variance swap? |
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Sep 28 |
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Comparing MVO with Resampled Efficient Frontier @richardmichaud I'm not sure that Meucci being a fan (no matter how much I like his work) or there being a patent are good reasons to want to use it. The best evidence you have going for resampling is papers showing it is comparable to Bayesian portfolio construction. |
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Sep 28 |
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Comparing MVO with Resampled Efficient Frontier I really like that last point. |
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Sep 28 |
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Comparing MVO with Resampled Efficient Frontier If you want to just compare the frontiers, why not just plot both of them? |
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Sep 28 |
revised |
Comparing MVO with Resampled Efficient Frontier added 10 characters in body |
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Sep 27 |
comment |
S&P 500 P/E percentile What do you mean Bloomberg accounted for it, but you didn't. If you select the S&P500 composition today and then get their P/E on 5/27/2007 and calculate 5 year return of them, then some of the stocks that are in the S&P500 today may not have existed five years ago (like a spin-off). Alternately, if you took the S&P500 as it existed on 5/27/2007, sorted by top percentile and calculated the return, then companies like Lehman may no longer exist and not have five year returns. |
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Sep 27 |
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Fastest solver possible for portfolio optimization I take it you mean you want to do a backtest that looks over the past n years using 30 different strategies. You might want to look to parallel processing. That tends to work well in this sort of situation. |
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Sep 27 |
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S&P 500 P/E percentile Does Bloomberg account for the changing composition of the S&P500? |
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Sep 27 |
asked | Strategies for Liar's Poker |
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Sep 26 |
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Average beta of index consitutents w.r.t. the index is 0.60 Just saying they should be consistent, but I'm not 100% sure it would be a big impact. |
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Sep 26 |
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Average beta of index consitutents w.r.t. the index is 0.60 Just saying you should be consistent. Total return vs. total return or price versus price. |
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Sep 26 |
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Average beta of index consitutents w.r.t. the index is 0.60 I'm not sure it would make a big difference (since the total return series should be highly correlated with the price series), but are you sure the index is total return if you're using the total return of the individual stocks? Outside of that I'd have to actually look at the data and code to have an idea. No other idea. |
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Sep 25 |
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Average beta of index consitutents w.r.t. the index is 0.60 How about using the market capitalization weights you have and calculating the returns on this portfolio. Then plot and compare and calculate the beta. My guess is that you have some kind of data problem, like the index being in a different currency or something. |
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Sep 22 |
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Average beta of index consitutents w.r.t. the index is 0.60 You might try calculating the weighted version as well. Another alternative, if you don't have market caps, is to calculate the return on the equally weighted portfolio of stocks you do have and then calculate the betas with respect to those returns. |
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Sep 21 |
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Is inverted Japanese style curve persistent when negative rates are real / market - observed? To be honest, I still don't understand what you're asking. I doubt you'll see a significant yield curve inversion when the short-term yield is kept at 0%. I just pulled on the Japanese curve on BB and saw inversion at the end of 1990 when rates were high, but nothing recent. |
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Sep 21 |
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Is inverted Japanese style curve persistent when negative rates are real / market - observed? The reason no one has answered this question is that it contains too many extraneous details. You need to simplify it. |
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Sep 20 |
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Discrete returns versus log returns of assets If you take normally distributed log returns and convert them to arithmetic, then they will become log normal. That's what I mean by estimating distributions easier. Also, it is easier to project log returns to the appropriate horizon due to time aggregation. As for invariance, see: symmys.com/node/85 |
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Sep 20 |
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Discrete returns versus log returns of assets I'm not sure there needs to be a "study." You seem well aware of the reasoning. Arithmetic returns allow for easier cross-sectional aggregation and log returns allow for easier time-aggregation. The reason people use log returns is that (for equities) they are approximately invariant and are easier to work with in estimating distributions. However, proper procedure is to convert the log returns to arithmetic returns for the purposes of portfolio optimization and risk management. |
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Sep 20 |
answered | Accounting for Withdrawals |
