# Tag Info

0

Your approach is how I would it. I share @kurtosis's questions about whether 3m Govt is the correct funding rate for a risk asset (for slightly different reasons); but your method is 100% kosher if you are supposed to use T-Bills here. I would prefer 3m (or 6w) Eurodollar/LIBOR/swap myself; but the difference between this and Bills will likely be a rounding ...

5

Yes, you can just do IGE - SPY if you assume the short finances the long. The Sharpe ratio will be the same whether or not you divide by 2.

1

Yes, your table is correct... the proverbial "catch" is in your assumptions of small gains, with nil volatility. Because volatility is itself the catch with levered strategies in general (and levered ETFs very specifically). Replicate these 1% returns with a 14.14% standard normal deviation, for a thousand, million, billion runs. Your 1% compound ...

0

For a leveraged ETF, with a a leverage of $L$, then the value of the ETF is: $$\mathrm{ETF}_{t_n} = \mathrm{ETF}_{t_0} \cdot \Pi_{i=1}^{i=n} \left[ 1+L\left(\frac{S_{t_i}}{S_{t_{i-1}}}-1\right) - f \cdot \mathrm{DCF}(t_{i-1}, t_i)\right]$$ where $t_i$ are the dates on which the ETF rebalances to restore the leverage. $f$ is the ETF management fee, and $\... 3 EWMA (and other sort of moving averages) introduces positive autocorrelation into otherwise uncorrelated returns. The fitted values of EWMA are linear combinations of past returns, and the constituent elements of these combinations overlap. Therefore, positive autocorrelation arises. If you have autocorrelated returns to begin with, they would in all ... 2 B. The change in the price of the cheapest-to-deliver behind that future is the key. The 100k is a notional required convention, to allow the future to exist. It has no real relevance in the real world, except in the choice of which bond is the cheapest to deliver for that contract, whose dynamics absolutely set the price for that same contract. The “... 2 Answer B is the closest. You can compute returns for any asset over one period as: $$r = \frac{\text{change in price} + FV(\text{net cashflows received})}{\text{starting price}}.$$ This basically breaks your returns into capital gains (term 1) and dividend and interest income (term 2). It might seem that you do not have interest income for a bond futures ... 2 Supplemental to copious previous discussion here: all based on this being an interesting, ie thought-provoking, question. The crux of the problem with any asset having a uniform return distribution (as opposed to the standard assumption of normality) is that such an asset with such a distribution in one time horizon would have a very different return ... 2 This does not pretend to be a complete answer to the question posed (but that question is not itself, to my mind, completely posed ;-) I'm just struck by how it resonates with the whole topic of "path dependency risk". This topic naturally captures a multitude of investment "sins". The most obvious of which is the sequencing of returns if ... 2 Such assets do not exist due to market efficiency: people would trade such assets until the price was near the expected value which would tend to yield more returns near 0 and fewer returns that were larger in magnitude. Thus such a distribution is in no way an ideal. The effect of market efficiency also renders your other questions moot. Even if that did ... 1 You can use the adjusted close price; it is far better than using unadjusted prices and having your strategy tell you to short a stock on its ex-dividend days. The bigger issue is using closing prices -- adjusted or unadjusted. Closing prices are determined by an auction and the presence of your order in the auction will change the auction price. Furthermore,... 0 Tautolotigally, a stock holder receives the dividend if they're the stock holder of record on the record date. Even if your trading strategy assumes that you will put on some position at the beginning of the day and then always flatten before the close, keeping no risk overnight, whatever information is contained in the return series assumes that somebody ... 1 To "draw" random returns samples from the assets' distribution, you first download empirical price data for$N$assets, convert them to returns then collect into matrix form, and then take subsets of these empirical multivariate returns data$m$times. After running the mean-variance model on each of these$m\$ Monte Carlo simulations, you average ...

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