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| bio | website | wingedfootcapital.com |
|---|---|---|
| location | New York | |
| age | 34 | |
| visits | member for | 1 year, 6 months |
| seen | 2 hours ago | |
| stats | profile views | 903 |
Quantitative Equity Portfolio Management research with a focus on market-neutral and long/short investing strategies. Focus is on systematic, multi-disciplinary, and hypothesis-based approaches to alpha generation and risk control across regimes.
Previous roles: Fixed income credit portfolio decisioning at a major bank/broker-dealer, Management Consulting in Financial Services, Columbia Economics, and Machine Learning. Live and work in NYC.
All posts and comments represent my views and not that of my employer. email: ram - at - wingedfootcapital . com
My favorite answers:
How do you mix quantitative asset allocation with qualitative views?
Empirical or theoretical insights that have shaped your thinking
Why is the first principal component a proxy for the market portfolio?
How do I graphically represent the evolution of a covariance matrix over time?
Which approach dominates? Mathematical modelling or data mining?
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Jun 10 |
answered | Is duration additive? $C_{newDur}=A_{fundDur}w_{a} + B_{fundDur}w_{b}$? |
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May 23 |
comment |
Minimizing Correlation Developing an exponentially weighted covariance matrix that weights more recent observations is probably the way to go |
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May 21 |
answered | Algorithm for the choice of stocks for a equity scalper/market maker to engage in? |
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May 18 |
comment |
Forward Adjusting Stock Prices? When measuring the total return of a security where the security pays dividends, shouldn't forward adjusted close prices assume immediate re-investment of the dividend in the security itself? This would imply a greater forward adjusted price as re-invested dividends would earn the rate of return on subsequent returns (assuming rising prices). |
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May 9 |
comment |
Minimizing Correlation Frank J. Fabozzi has a couple of books that cover risk modeling as well as covariance matrix estimation. A good one is "Robust Portfolio Optimization" |
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May 9 |
answered | Minimizing Correlation |
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Apr 29 |
answered | Quantitative Derivatives Trading vs. Time |
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Apr 29 |
answered | George Soros models |
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Apr 29 |
comment |
How to incorporate technical indicators into neural networks? State-space models, decision trees, MARS |
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Apr 26 |
answered | How to incorporate technical indicators into neural networks? |
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Apr 25 |
comment |
Total Return measurement paradox w/ Adjusted Close Prices Publicly traded stock. Dataset is from CSI. www.csidata.com |
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Apr 24 |
answered | Separating the wheat from the chaff: What quant methods separate skillful managers from lucky ones? |
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Apr 24 |
answered | Any known bugs with Yahoo Finance adjusted close data ? |
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Apr 24 |
accepted | Total Return measurement paradox w/ Adjusted Close Prices |
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Apr 24 |
comment |
Total Return measurement paradox w/ Adjusted Close Prices Hi Bill - flagging the company is a decent way to go. Then I can impose/impute some kind of max return. I'll have to scale/trim calculated returns anyway to avoid outliers. AVIS was just an example -- there are dozens of companies that exhibit this phenomenon. |
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Apr 24 |
comment |
Total Return measurement paradox w/ Adjusted Close Prices Correct - this "percentage-based adjustment" the Yahoo approach. It does create bias however in that the actual P&L return is not truly measured. This may be the best choice among the alternative of having an undefined/infinite return however. |
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Apr 24 |
comment |
Total Return measurement paradox w/ Adjusted Close Prices Yes this is an approach that resolves the paradox. It does open a second technical issue in that my current "forward-adjusted" close prices will not match quotes observed on exchanges. This makes debugging and data quality control more difficult when you want to validate return figures. Also, to place trades, I will need to maintain an un-adjusted price series. |
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Apr 22 |
asked | Total Return measurement paradox w/ Adjusted Close Prices |
