# Tag Info

5

The Sharpe ratio and the Sortino ratio are not under the control of the ETF managers, they will be equal (or very close) to the ratios for the Index that the ETF tracks. There is not much room for differentiation here. To make their ETF attractive to customers, fund managers care about the tracking error between their fund and the index. They would like ...

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Portfolio risk metrics matter a lot for all fund managers. Though certain type fund vehicles can have completely different sets of performance metrics. It's hard to imagine a Venture Fund analyzing their portfolio using Sharpe and Sortino. Passive ETF funds probably care about Asset Under Management (AUM), inflow/outflow, and top allocation the most. Since ...

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It usually depends on: the reason why the strategy was shut down what are you using the sharpe ratio number for Examples: you're a discretionary trader and at a certain point decide to go all in cash for the next month. It's reasonable to include shut down period into calculation, since the decision was a part of your strategy you run an algo strategy ...

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You probably entered it wrong. you must enter the following: (0,1136 - 0,0086)/ 0,1629 = 0,64518 If you want to do it via Excel. I can send you a finished calculation that I had to do for a paper at university. That would be for daily returns, but that is of no importance. If you would like to try it yourself, let me know and I would be happy to explain ...

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Not sure if "3-4 Sharpe" indicates the value of the Sharpe ratio you're earning since such magnitude is meaningless without some benchmark to compare against, due to it being a purely relative measure. Anyway, we can talk about 6 things that should stop you from using high leverage: Surprise bear market Asymmetric tail dependence Sharpe ratio ...

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Yes, Sharpe follows a student's t distribution. https://alo.mit.edu/wp-content/uploads/2017/06/The-Statistics-of-Sharpe-Ratios.pdf

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First of all, Sharpe Ratio (SR) is meant to assess the uncertainty surrounding the expected returns of your PnL. In short: you divide by the standard deviation of the returns because you trust less a time series of PnL with a large standard deviation than with a small one. Nevertheless it is in fact not the best indicator; the best one is the t-test, that ...

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It is hard to tell, because means and standard deviations are hard to estimate. Take a look at the example below from De Miguel et al: The row you are interested in is the third row ($mv$). They simulate normally distributed data, and realise that only when you have 6000 months of data (i.e. 500 years), mean variance starts to be close to the true sharpe ...

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The answer above is not correct. Let's go by parts: Denote the mean of returns $\mu$. Denote the standard deviation of returns: $\sigma$. Therefore the sharpe ratio is: $$SR = \frac{\mu-r_f}{\sigma}$$ The corresponding standard errors are: $$se(\hat{mu}) = \frac{\sigma}{\sqrt{t}}$$ $$se(\hat{\sigma}) = \frac{\sqrt{2} \sigma^2}{\sqrt{T}}$$ $$se(\... 2 \lambda is independent of the maximum sharpe ratio. The maximum sharpe ratio portfolio will give you a combination of the risk free asset and the tangency portfolio. Then your risk aversion just makes you choose the combination between these two assets. See picture below. The blue line is the efficient frontier with short-sales allowed. The red-curve is ... 2 Whereas the Sharpe ratio divides the risk premium (mean excess return) by the volatility, the Sortino ratio instead divides by semideviation: the standard deviation computed using only negative returns. For perfectly symmetric return distributions, these should not differ much. However, if a return distribution has skewness, then the Sortino ratio may be ... 2 Insofar as a standard exists, it would be a Sharpe ratio from monthly returns using arithmetic rather than log returns. As a rule of thumb, arithmetic returns should always be used in any kind of reporting since log returns are an approximation (and one we tolerate for ease of use despite being slightly off, particularly for larger moves). Also return is ... 2 The question isn't simply answered and the short answer is it depends on a number of factors. The GIPS standard for investment managers is the only performance reporting standard AFAIK and it can be found here: https://www.cfainstitute.org/en/ethics-standards/codes/gips-standards/firms There are certain rules and requirements depending on the frequency you ... 2 Your formula for sharpe ratio is correct Given that dataset, your mean and std dev are overall fine The sharpe ratio is 0.64. Meaning, you achieve 0.64 return (over the risk-free rate) for each unit of risk you confront. You must consider that this year is (obviously) an outlier. For instance, look at the descriptive statistics of your dataset, where it is ... 2 Passive ETF Performance Metrics: Tracking Error % of days closing price substantially above NAV % of days closing price substantially below NAV Liquidity Median bid/ask spread based on NBBO (explains why funds prefer smaller prices) Avg Daily Volume (ADV), as well as ADV/shares issued Costs Expense ratio Misc Consolidated ESG metrics The ESG part is ... 1 On any day you should keep track of two things: The cash on hand V_t and the amount of the asset you own A_t (A can be negative if you allow short positions. Or if you want you can restrict A to a range such as 0\le A_t \le U for example, or -1 \le A_t \le 1 for a simple startegy that is either neutral or long/short 1 unit). You don't allow the ... 1 Treat scalars as annoying constants to be dealt with later and solve the KKT conditions up to that scaling. You already showed that$$ \frac{\bar{y} - R_fp}{c_1} - \frac{c_2}{c_1^3}V\omega = 0.  This would suffice to prove the identity of $\omega$ up to scaling.

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I assume Michael meant distribution of maximum negative returns of iid Normal distribution. I guess the word drowdowns is meant to represent sequence of max negative returns, not the drowdowns of any specific strategy

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SOFR quote is annualized rate.

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Question1: I think you're confused on what you're actually measuring. Don't think about this in terms of trades, think about it in terms of the total value of your portfolio. At day 1 you have 100 dollars, tomorrow you have 110, 2 days from now 115 and a week from now it's back to 105. How many trades you made during that period, how big those positions are ...

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For anybody still following this: I figured out that the equations and my code work fine; the problem was that I had to scale the returns before doing the risk calculations to avoid float32 precision data loss, and also just that my value for η was far too high. Lowering my η value to <= 0.0001 produces totally logical sharpe and sortino approximations. ...

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If your concern is about computational efficiency in calculating Sharpe/Sortino over large and increasing amounts of data, you can use incremental/online methods to calculate means, standard deviations etc. over the whole data set. Then just use the latest, online calculated value for the Sharpe/Sortino of the whole data set. This will avoid the problem of ...

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If you want to calculate the Sharpe and Sortino ratios for the portfolio, you should directly calculate them using the returns of the portfolio Even if the individual sharpe ratios for each of the $N$ assets being dot-multiplied by the portfolio weights is equivalent to the above approach, you would be calculating $N$ number of Sharpe/Sortino ratios when ...

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My understanding is that a Sharpe Ratio must be calculated based on the actual trading days elapsed, not on the days traded. The calculation proceeds as follows: 1) Establish a list of all trading days between 6/2/2016 and 6/9/2020. You could start with a list of all calendar days, remove Saturdays and Sundays and then remove the NYSE holidays listed on ...

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The sortino ratio is also important for evaluating trading strategies. also the omega ratio. The question is a poor one though. Each of the mentioned ratios will be the most predictive at predicting ... THEMSELVES! respectively. you don't use the calmar to predict the sharpe. ok, what you are probably actually asking is which of the performance metrics ...

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