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7 votes
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Risk-adjusted returns ratio that does not reward high risk for negative returns

Yes, you are correct on both terms - it doesn't make much sense, and there exists a well-cited solution by C. Israelsen: "A refinement to the Sharpe ratio and information ratio." Journal of Asset ...
Forgottenscience's user avatar
5 votes
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average return Vs cumulative return interpretation

Consider these two simple portfolios: Portfolio 1 returns -10% in month 1 and 10% in month 2. Average arithmetic return is zero, and cumulative return is $(1-10\%)(1+10\%)=0.99$. Portfolio 2 returns -...
Helin's user avatar
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5 votes
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What is an accepted method to calculate percent PnL from a short position?

A short position is a liability on your books, as the borrowed asset has to be returned to the owner. The return is then the percentage return of that liability. Assume that the shorted asset at ...
RRG's user avatar
  • 1,024
5 votes
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Sharpe ratio: discrete or continuous returns?

For client reporting purposes, it is customary to use discrete returns. For backtesting, it pretty much make no difference.
Helin's user avatar
  • 11.7k
5 votes

CAPM and Beta: problem with regression (Beta is too low yet statistically significant?)

You are right to be sceptical of the beta of an international portfolio when it is calculated using daily returns. Beta estimates are often low for international portfolios because stock market ...
Tim Wilding's user avatar
  • 1,406
5 votes
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Information Coefficient (IC) Formulae Differences

Paraphrasing some quote: "they are different but same but still different" In reality the number of correct bets $N_c$ is the number of times the analyst was correct predicting the ...
emot's user avatar
  • 876
4 votes

ES not elicitable

I think it was T. Gneiting in 2011 who first proved that ES is not elicitable (Making and Evaluating Point Forecasts, Journal of the American Statistical Association Volume 106, 2011 - Issue 494) , ...
RiskyScientist's user avatar
4 votes
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Sharpe Ratio, risk free rate

No, this is not the same. For example, consider the scenario $$ \begin{align*} r_A &= 10\% \quad\quad \sigma_A = 10\% \\ r_B &= 1.5\% \quad\quad \sigma_B = 1\% \\ \end{align*} $$ If $r_f=1\%$, ...
msitt's user avatar
  • 741
4 votes

What returns to use?

Since you're looking to summarize the performance of a monthly return series in a single number, it is best to compute the annualized return. This is the standard used in the investment management ...
nitin23's user avatar
  • 61
4 votes
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Alternative relative performance measure to Sharpe ratio for non-IID return

I don't know that there is a "standard-solution crystalized in the community," but there are alternatives. The ones that I prefer are Omega, Sortino, and Kappa. All three of these ratios, unlike ...
amdopt's user avatar
  • 4,348
4 votes

Multi-Period Contribution

Thanks for the example. It is exactly like my comment. Look at your weights after the first period. Are they really 80% and 20%? Lets say you have £100 to invest. £80 is invested in product A. That ...
AKdemy's user avatar
  • 8,924
4 votes
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Understanding out-of-sample performance metrics for Realized Volatility

You can compare the losses against each model and determine the "best" model to be the one with the smallest losses. In many cases for larger studies, the results might be ambiguous where ...
Pleb's user avatar
  • 4,286
3 votes

Measuring alpha (Academia vs the Industry)

Both questions are not as straightforward as @Hui (and most academics and practitioners) would immediately think. I would try to put in my two cents to answering your question 1. Short answer: It ...
Igor Pozdeev's user avatar
3 votes

Is there a python library to generate performance metrics from returns of the strategy?

Check out empyrical. This library provides methods for calculating several risk and performance metrics. pyfolio is also a great tool for visualizing your portfolio's performance over time.
ernestoeperez88's user avatar
3 votes

Annualising Data

It depends on the ratio you are looking at. Most of them are scaled by $\sqrt{12}$, but the Treynor index is a bit different and is scaled by $12$. Sharpe and Information ratios are both ratios of ...
Tim Wilding's user avatar
  • 1,406
3 votes
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Calculate Sharpe ratio for only one return

For a single period return, the squared value of that return approximates variance (i.e., the absolute value approximates the standard deviation). Standard deviation is defined thus: $$\sigma_X = \...
David Addison's user avatar
3 votes

What's the exact definition of alpha?

As @Alex C had pointed out, the CAPM and subsequently Jensen were probably the original motivations of the term $\alpha$. Bear in mind that $\alpha$ and $\beta$ are conventional notation for ...
madilyn's user avatar
  • 5,240
3 votes

What's the exact definition of alpha?

In Quant Finance we start with the assumption that (until shown otherwise) no one can outperform a simple, passive benchmark. Such a benchmark might be for example the S&P 500 index leveraged up ...
Alex C's user avatar
  • 9,382
3 votes
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How likely it is that a strategy profits are explained by luck?

Something along these lines is known as the Cowles Test, suggested by Alfred Cowles in 1933 (Can stock market forecasters forecast? https://cowles.yale.edu/sites/default/files/files/pub/misc/cowles-...
nbbo2's user avatar
  • 11.4k
3 votes

How likely it is that a strategy profits are explained by luck?

I believe that by "luck" you mean that you want to check if you can attribute the pnl of your strategy to something else than the "alpha" that it's trying to capture. The standard way of doing this ...
Ezy's user avatar
  • 2,187
3 votes
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What is a cumulative return series?

O7-30-2021 : POSTING COMMENT AS ANSWER BASED ON SUGGESTION OF RICHARD HARDY. Hi: The cumulative return is defined as the return on 1 dollar if it had been invested in whatever asset the returns came ...
mark leeds's user avatar
  • 1,112
3 votes
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Out of Sample Results Decay Rapidly With Prediction Window or Embargo

This is a complex question. Let me reformulate its main components to try to give a generic answer: if a relationship is non-stationary and I capture it via a model, I expect the explanatory power of ...
lehalle's user avatar
  • 12.2k
3 votes

Is there an encyclopedia of peformance/risk measures for backtests of strategies?

You can use quantstats in Python. https://github.com/ranaroussi/quantstats
SachaTheBrave's user avatar
3 votes

How to interpret the turnover formula?

This is a very standard approach for measuring turnover from portolio weights. First, assume there are no buys or sales during the month. Then we can predict the weights at the end of the month from ...
nbbo2's user avatar
  • 11.4k
2 votes

Risk-adjusted returns ratio that does not reward high risk for negative returns

Does this make sense? Consider this: You are an investor. You have 2 investments. 1 high risk (hr) and the other low risk (lr). You expect the hr to be volatile and expect the opposite from lr. ...
amdopt's user avatar
  • 4,348
2 votes

Risk-adjusted returns ratio that does not reward high risk for negative returns

1) In a certain, theoretical sense, it does make sense: suppose two portfolio managers delivered negative returns (-1%, say), and one had a higher volatility ("risk") than the other. Then the ...
Enrico Schumann's user avatar
2 votes

Diversification investment metric for a FI portfolio

This extends to not just FI but multi asset class (MAC) as well. You can use a linear MAC factor model to compute specific\unsystematic risk. Here's are several examples of such a model: https://www....
pyCthon's user avatar
  • 2,121
2 votes

Accuracy for GARCH models

The best way to check the accuracy of a Garch model is to use the methodology of Hansen and Lunde (2005). In this paper they actually compared the accuracy of 330 Arch-type models and concluded that ...
phdstudent's user avatar
  • 8,371
2 votes
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performance measure using pnl series

Adding to Attack68 answer- you can do a few things: calculate total and average pnl over a given time. calculate skew, kurtosis etc. as suggested above. calculate hit rate. calculate max drawdown. ...
polarbear's user avatar
  • 111
2 votes
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How to calculate the Maximum Drawdown for a portfolio in MATLAB?

Max drawdown of a portfolio is the loss relative to a previous high-water mark. It's typically calculated as you describe, calculating cumulative performance and maxDD relative to the previous equity ...
Chris's user avatar
  • 1,643

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