# Tag Info

5

Hmm, this table looks wrong. Here's what it should look like. After the most recent corporate action, the Close and Adjusted Close should be the same; only prices from before the most recent action should have a different Adjusted Close. Here's another example. I think Yahoo just has the wrong information. If you wanted to derive your own adjustments for ...

4

Some of the used heavy-tail distributions are: Log-Cauchy and Log-Gamma Lévy Burr and Weibull Mixed normal Here two papers that cover some of them and others: http://ect-pigorsch.mee.uni-bonn.de/data/research/papers/Financial_Economics,_Fat-tailed_Distributions.pdf http://www.rff.org/RFF/Documents/RFF-DP-11-19-REV.pdf

3

It depends on what you do with your returns. If your returns directly affect your capital base, regardless of positive or negative returns, and if you employ all the generated returns in new trades on which you subsequently calculate returns then you should use compounded returns. Else your returns should be treated as additive and simply aggregated through ...

3

Returns are supposed to be compounded. For example, if I make 10% today and another 10% on top of that tomorrow, then I will have made 21%. Addition would only make sense if I had taken my profits out at the end of the first day. So no, you can't add returns like this. Instead, you must multiply the returns: \prod_{i=1}^{n} (x_i + 1) - 1 ...

3

Concerning adjusted price series: Free yourself from terminology and definitions, as you can clearly see, Yahoo Finance got it wrong on the stock split you linked to (and as chrisaycock correctly pointed out). You need to focus on the problem not the term people use to describe the problem: You need to adjust time series for the stock split, period. So, ...

3

I can only repeat myself because your mentioned previously asked question is essentially identical: => I would say do not include non-trading days, do not include days with zero position, do not include days where the asset did not trade for whatever other reason. Here some reasons and pointers: Sharpe measures excess returns scaled by volatility. The ...

2

You are not doing anything wrong. You just need to multiply the absolute return by the currency conversion factor. Example: You trade 200,000,000 yen notional and generate a return of 16% on that notional, then simply multiply 32,000,000 jpy gain by your conversion factor 0.0126 to yield a return of 403,200 USD. The return of 16% was generated on the ...

1

It seems to me that you want to use the series of option prices to estimate the Sharpe ratio given the option prices in your sample. If so, the idea is to realise that for each option price you have at different times $t_1, t_2, ...$ you could actually close the position and realise the profit or loss. So, basically if you have the option prices you just ...

1

Compounding the monthly excess returns won't provide the annual excess return. You need to compute the difference between the annual return of the portfolio and the annual return of the benchmark. To illustrate this let's look at an example. Consider the following two situations: The benchmark performs well with a $2\%$ return each month; The benchmark ...

1

You should definitely check out the Virtual Stock Exchange Games* by Marketwatch it provides simple interface, and many options for the rules of the game. Its instantly online, free, and uses real-time prices, but it only allows trading NASDAQ stocks, as far as I know. These games are meant to be played by students, and thought, so I hope it fits your ...

1

Generally I would annualize risk and returns even when an asset's returns/general time series (ts) does not span over the full year So, both, FB and G present risk and return over the past year. For risk and return that is calculated over longer periods I would not include an asset in the portfolio of which you have no ts available to measure risk and ...

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