# 1278 search results for "LaTeX"

## Teaching with R: the tools

November 1, 2011
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I bought an Android phone, nothing fancy just my first foray in the smartphone world, which is a big change coming from the dumb phone world(*). Everything is different and I am back at being a newbie; this is what … Continue reading →

## Minimizing Downside Risk

November 1, 2011
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$Minimizing Downside Risk$

In the Maximum Loss and Mean-Absolute Deviation risk measures, and Expected shortfall (CVaR) and Conditional Drawdown at Risk (CDaR) posts I started the discussion about alternative risk measures we can use to construct efficient frontier. Another alternative risk measure I want to discuss is Downside Risk. In the traditional mean-variance optimization both returns above and

## Sampling for Monte Carlo simulations with R

October 31, 2011
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$Sampling for Monte Carlo simulations with R$

I've knocked together a quick function for generating efficient Monte Carlo samples. It takes a bit of the legwork out of running Monte Carlo simulations.

## Bayesian ideas and data analysis

October 30, 2011
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Here is another Bayesian textbook that appeared recently. I read it in the past few days and, despite my obvious biases and prejudices, I liked it very much! It has a lot in common (at least in spirit) with our Bayesian Core, which may explain why I feel so benevolent towards Bayesian ideas and

October 28, 2011
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$Copulas made easy$

Everyday, a poor soul tries to understand copulas by reading the corresponding Wikipedia page, and gives up in despair. The incomprehensible mess that one finds there gives the impression that copulas are about as accessible as tensor theory, which is a shame, because they are actually a very nice tool. The only prerequisite is knowing

## The Most Diversified or The Least Correlated Efficient Frontier

October 27, 2011
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$The Most Diversified or The Least Correlated Efficient Frontier$

The “Minimum Correlation Algorithm” is a term I stumbled at the CSS Analytics blog. This is an Interesting Risk Measure that in my interpretation means: minimizing Average Portfolio Correlation with each Asset Class for a given level of return. One might try to use Correlation instead of Covariance matrix in mean-variance optimization, but this approach,

## Covariance structures

October 26, 2011
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$Covariance structures$

In most mixed linear model packages (e.g. asreml, lme4, nlme, etc) one needs to specify only the model equation (the bit that looks like y ~ factors...) when fitting simple models. We explicitly say nothing about the covariances that complete … Continue reading →

## Expected shortfall (CVaR) and Conditional Drawdown at Risk (CDaR) risk measures

October 25, 2011
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$Expected shortfall (CVaR) and Conditional Drawdown at Risk (CDaR) risk measures$

In the Maximum Loss and Mean-Absolute Deviation risk measures post I started the discussion about alternative risk measures we can use to construct efficient frontier. Another alternative risk measures I want to discuss are Expected shortfall (CVaR) and Conditional Drawdown at Risk (CDaR). I will use methods presented in Comparative Analysis of Linear Portfolio Rebalancing

## Vanilla C code for the Stochastic Simulation Algorithm

October 24, 2011
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$Vanilla C code for the Stochastic Simulation Algorithm$

The Gillespie stochastic simulation algorithm (SSA) is the gold standard for simulating state-based stochastic models. If you are a R buff, a SSA novice and want to get quickly up and running stochastic models (in particular ecological models) that are not … Continue reading →

## Minimum Investment and Number of Assets Portfolio Cardinality Constraints

October 19, 2011
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The Minimum Investment and Number of Assets Portfolio Cardinality Constraints are practical constraints that are not easily incorporated in the standard mean-variance optimization framework. To help us impose these real life constraints, I will introduce extra binary variables and will use mixed binary linear and quadratic programming solvers. Let’s continue with our discussion from Introduction