# 999 search results for "latex"

## Vanilla C code for the Stochastic Simulation Algorithm

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

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
By

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

## 130/30 Porfolio Construction

October 18, 2011
By

The 130/30 funds were getting lots of attention a few years ago. The 130/30 fund is a long/short portfolio that for each $100 dollars invested allocates$130 dollars to longs and \$30 dollars to shorts. From portfolio construction perspective this simple idea is no so simple to implement. Let’s continue with our discussion from Introduction

## Short selling, volatility and bubbles

October 17, 2011
By

Yesterday, I wrote a post (in French) about short-selling in financial market since some journalists claimed that it was well-known that short -selling does increase volatility on financial market. Not only in French speaking journals actually, sin...

## Tikz Nodes

October 17, 2011
By

Nodes are used in tikz to place content in a picture as part of a LaTeX document. Fast Tube by Casper When creating a tikz picture the origin is assumed to be at (0,0) and objects are placed with positioning relative to the origin on the picture. If we wanted to add a grid with

## Once you’re comfortable with 2-arrays and 2-matrices, you…

October 15, 2011
By

Once you’re comfortable with 2-arrays and 2-matrices, you can move up a dimension or two, to 4-arrays or 4-tensors. You can move up to a 3-array / 3-tensor just by imagining a matrix which “extends back into the blackboard”. Like a 5 × 5 ma...

## Once you’re comfortable with 2-arrays and 2-matrices, you…

October 15, 2011
By

Once you’re comfortable with 2-arrays and 2-matrices, you can move up a dimension or two, to 4-arrays or 4-tensors. You can move up to a 3-array / 3-tensor just by imagining a matrix which “extends back into the blackboard”. Like a 5 × 5 ma...

## Maximum Loss and Mean-Absolute Deviation risk measures

October 14, 2011
By
$Maximum Loss and Mean-Absolute Deviation risk measures$

During construction of typical efficient frontier, risk is usually measured by the standard deviation of the portfolio’s return. Maximum Loss and Mean-Absolute Deviation are alternative measures of risk that I will use to construct efficient frontier. I will use methods presented in Comparative Analysis of Linear Portfolio Rebalancing Strategies: An Application to Hedge Funds by

## plyr, ggplot2 and triathlon results, part II

October 13, 2011
By

I ended my previous post by mentioning how one could imagine other ways of looking at the triathlon data with plyr and ggplot2. I couldn’t help but carry on playing with it so here are more stats and graphs from … Continue reading →

## Maximum likelihood

October 13, 2011
By
$Maximum likelihood$

This post is one of those ‘explain to myself how things work’ documents, which are not necessarily completely correct but are close enough to facilitate understanding. Background Let’s assume that we are working with a fairly simple linear model, where … Continue reading →