8,262 reputation
2160
bio website wingedfootcapital.com
location New York
age 35
visits member for 3 years
seen May 27 at 18:53

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?


Sep
7
comment Historical data on short rates
Hi Alon - welcome to quant.stackexchange.com. This is similar to my question here: quant.stackexchange.com/questions/3891/…
Sep
5
comment How to define the objective function for a custom optimization problem?
@pyCthon - sure shoot me a note. I'm attending an Emanuel Derman talk this Thu eve - could meet there.
Sep
4
comment How to define the objective function for a custom optimization problem?
@pyCthon - particular objective functions have clever solution strategies that are fast and accurate. For example, the author of CVAR (Uryasev) has a commercial product that is remarkably fast. But given an "aribtrary" objective function that may not be differentiable I think these general purpose algorithms are the best one can offer. Some firms (particuarly HFT) do invest in hardware such as FPGA to do as close to real-time optimization as possible. If you know of a good general-purpose algo that is also fast, let me know!
Sep
4
comment How to define the objective function for a custom optimization problem?
@pyCthon - good point. You can also use CUDA GPU to accelerate.
Sep
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comment How to define the objective function for a custom optimization problem?
@SRKX If the function is convex (and therefore differentiable) you can guarantee an optimum point using a quadratic optimizer. Updated my answer to elaborate a bit more
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Aug
23
comment Is this a common variation of sharpe ratio?
@Freddy btw, I don't disagree with your answer in fact I +1'd it -- I think there are some other dimensions to bring out that's all. Cheers
Aug
23
comment Is this a common variation of sharpe ratio?
@Freddy - Most of the critiques against the Sharpe nature are statistical in nature. True they apply to other measures but it seems an answer to the question. On Point 7: Most investors do not have mean-variance utility functions (see Prospect theory and Behavioral finance literature). On point 2, at higher intervals intra-month or intra-period volatility is drowned out. Monthly vol measurements miss entirely episodes such as Aug 2007 quant meltdown, flash crash, etc. There are scenarios where daily Sharpe can be > monthly sharpe but it isn't usually the case.
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Aug
22
comment Is this a common variation of sharpe ratio?
@John - I like your point as an add'l new point (added). I should clarify my point to say that the comparability of the statistic across strategies assumes the joint normally distributed returns.
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