8,039 reputation
1753
bio website wingedfootcapital.com
location New York
age 34
visits member for 2 years, 4 months
seen 14 hours ago

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?


Aug
25
revised Portfolio optimization with monte carlo sampling from predictive distribution
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Aug
25
answered Portfolio optimization with monte carlo sampling from predictive distribution
Aug
25
revised What is the relationship between risk aversion and preference for skewness and kurtosis in portfolio optimization?
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Aug
25
revised What is the relationship between risk aversion and preference for skewness and kurtosis in portfolio optimization?
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Aug
25
answered What is the relationship between risk aversion and preference for skewness and kurtosis in portfolio optimization?
Aug
24
comment How do I find the most diversified portfolio, or least correlated subset, of stocks?
You could probably use DEOptim() R package to solve this complex objective function. Along the lines suggested, I would add a constraint for the max number of assets. Also, you can include in the objective function a vector corresponding to the expected returns of each stock. Since you are optimizing only over 10 stocks the algorithm would converge rapidly.
Aug
23
revised The T+H Problem in Factor model forecasts
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Aug
23
revised The T+H Problem in Factor model forecasts
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Aug
23
revised The T+H Problem in Factor model forecasts
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Aug
23
revised The T+H Problem in Factor model forecasts
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Aug
23
comment The T+H Problem in Factor model forecasts
Yes - I have a sliding window. The forecast for T+H is adjusted - let's say weekly. I don't see how that helps much - you still need to wait a full-year for the dependent variable to manifest itself in the training data.
Aug
23
answered The T+H Problem in Factor model forecasts
Aug
23
comment The T+H Problem in Factor model forecasts
a) In my case I am using daily data. b) weighting is a good idea to capture the changing correlation structure but it would have not worked in the above scenario -- a full one year after the bear market you would still be short. c) has the seeds of a good approach. There would be some method to calibrate returns to some factor that is measured each day. The devil is in the details though - how would you realize this specifically?
Aug
23
revised The T+H Problem in Factor model forecasts
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Aug
23
asked The T+H Problem in Factor model forecasts
Aug
23
revised How to calculate optimal standard deviation bands for trading?
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Aug
23
answered How to calculate optimal standard deviation bands for trading?
Aug
23
answered How well does CAPM beta track the risk of a particular market relative to world markets?
Aug
23
revised How can I select the least correlated portfolio of assets?
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Aug
23
answered How can I select the least correlated portfolio of assets?