muffin1974
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In a standard approach you would think about the evolution of a return process in the following form: $$dr_t=\mu dt+\sigma dW_t,$$ where for the sake of simplicity I assumed constant volatility and ...

Although I like the other answers to this question I think, there are some points which may be interesting to note and should get attention as well. Let me address each of your individual questions. ...

There are some issues with your code - you are using wrong variables as inputs/ in case you are not sure what the function arguments mean, search online for a documentation of the PortfolioPerformance ...

Well, I do not think there is a large difference: Given you deposit money at a Bank the value of this deposit changes according to $$\frac{dB_t}{B_t} = r dt$$ which simply means there is no ...

I do not have access to this book but I suppose the decomposition is the cholesky decomposition (if you use R, simply generate it with chol(cov(g)) where g is a matrix with forecasts. What the ...

As @Rosetta states in the comment above, I think the difference between the two formulas you represent can be explained by either focusing on estimating the coefficient $\beta$ or by taking into ...

There is one minor mistake: If you compute sum(mean.var) you'll obtain $-1$ instead of $1$. So it should be mean.var<-xt/sum(xt) in order to ensure that the weights sum up to one. The remainder ...

Let me start with a general point: Why do you want to use these datapoints if it is so hard to understand how they are constructed? First of all 4) I am not familiar with testing momentum strategies ...

As a first Idea I would propose to incorporate basic ideas of Behavioural Finance and Dividend Theory into your considerations; for reference, look at: Baker, Malcolm, and Jeffrey Wurgler. ...

You do note require a sum up constraint that gives you that the weights sum up to 1? Then the problem is equivalent to a maximization without constraints: $$Z(\omega)=w'\mu - \frac{\gamma}{2}w'Vw$$ ...

As you are especially interested in applications in Finance I'll recommend this book of Rachev which focus on Bayesian Methods in Finance

With coefficient of variation you refer to the relative standard deviation $\frac{\sigma}{\mu}$ I suppose? In this case, negative values occur, as your historical data exhibits a negative drift, ...

Your statement should be correct, the weights into the risky asset are not bounded between $0$ and $1$. Essentially, by setting $r=0$ you omit the term which shows that your weights always sum up to ...

If you make your repayment at the beginning of the month you do not have to pay accrued interest of the amount for the month. So, paying already 961.83$at the first of each month makes a subtle ... View answer Accepted answer 2 votes In literature you'll find many approaches to compute the variance. As mentioned already, the standard ideas are to use MLE, Shrinkage on the Covariance Matrix (Ledoit, Wolf), Shrinkage on the inverse ... View answer 1 votes Have a look in the introduction of the book of @lehalle and Laruelle: Market Microstructure in Practice, there is an excellent overview in tabular form. Lehalle, Charles-Albert, and Sophie ... View answer Accepted answer 1 votes The introduction of a redundant assets means, that one of the existing assets is duplicated. So, in other words, you do not introduce an extra asset which changes the covariance matrix, but instead ... View answer 1 votes Why do you think this is not apropriate? Matlabs documentation for 1-D Data interpolation states that interpl1 using method spline is the right way to go: Spline interpolation using not-a-knot end ... View answer Accepted answer 1 votes Welcome to quant.SE! I do not have specific experience with the CARR Model, however, I had a short look in the paper you mentioned: As far as I understand the model specification you just implement a ... View answer 1 votes A perfectly hedged portfolio should not make any profits different from the risk free interest rate. However, you won't be able to hedge perfectly in the real world. Delta hedging for example requires ... View answer 1 votes Well, I am not an expert in this field but I set up quite some simulation studies in Matlab and I never had to use Simulink before. View answer 1 votes Intuitively speaking this statement should be clear, as in case the risk-free rate is equal to the expected return of the global minimum variance portfolio you can just assume that the minimum ... View answer Accepted answer 1 votes So you are asking whether the function Box.test requires standardized or raw residuals as input? I do not know this function but as you mention that the results change based on your input it should be ... View answer 1 votes This should follow from the properties of the forecast - for example the GARCH(1,1) forecast for$h$steps is computing the conditional expectation of$\sigma^2_{t+h}\$ based on the information set-up ...