Pyfolio Returns Analysis

Performs returns analysis of assets and portfolios for last 10 yrs. S&P 500 returns are used as benchmark.

Pyfolio Returns Analysis

Use Case

Sravz Pyfolio Returns Analysis page can be used compare the performance of your stock/bond/etf w.r.t to S&P 500 returns over last 10 yrs.

Pyfolio Returns Analysis - Screenshot

Video explanation

Pyfolio Returns Analysis - Description

Returns tear sheet
- Peformance statistics
  - Annual Returns: % annual returns
  - Cum Returns Final: % cummulative returns in last 10 years
  - Annual volatility: % annual volatility (risk)
  - Sharp Ratio: Compares performance of an asset w.r.t risk free asset.
  - Calmar Ratio:
    - Compounded annual growth rate divided by the maximum drawdown.
    - The maximum drawdown is the maximum peak to trough of the returns measured over a three year period.
  - Stability of TimeSeries:
    - Determines R-squared of a linear fit to the cumulative returns.
    - Computes an ordinary least squares linear fit and returns R-squared.
  - Max drawdown:
    - Maximum loss that occurrend on the portfolio
  - Omega Ratio:
    - Defined as the probability weighted ratio of gains versus losses for some threshold return target
    - Threshold is set to 0
    - Higher Omega Ratio is good for the portfolio
  - Sortino Ratio:
    - Sharp Ratio uses complete volatility in the denominator. Upside + Downside volatility
    - Sortino Ratio uses only Downside volatility in the denominator
  - Skew:
    - Positive Skew: Positive skew indicates that the tail is on the right side of the distribution
    - Negative Skew: Indicates that the tail is on the left side of the distribution
    - Zero Skew: Normal distribution. Tails are equal on both side of the distribution
  - Kurtosis:
    - Higher kurtosis corresponds to more frequent extreme deviations (or outliers), as opposed to frequent modestly sized deviations.
    - Kurtosis of Normal distribution is 3
  - Tail ratio:
    - Determines the ratio between the right (95%) and left tail (5%).
    - For example, a ratio of 0.25 means that losses are four times as bad as profits.
  - Common Sense Ratio:
    - Multiplication of the tail ratio and the Gain-to-Pain-Ratio – sum(profits) / sum(losses)
  - Information Ratio:
    - (Portfolio returns - Benchmark Returns)/Tracking Error
    - Tracking error = STD of difference between portfolio and benchmark returns
    - Show how portfolio manager provides extra information to achieve returns over benchmark returns
  - Value at risk:
    - Value at risk is a statistical metric that forecasts the highest possible loss and the probability of it occurring over a particular period.
  - Alpha:
    - Represents by how much percent the portfolio beats the benchmark
    - Zero alpha indicates the portfolio perfectly tracks the benchmark index
  - Beta:
    - Shows how much risk the asset/portfolio will add (or potentially subtract) from a diversified portfolio.
    - (Covariance of Asset/Portfolio Returns, Market returns)/Variance of Market Returns
Worst Drawdown Statistics
- Display loss experienced during each loss period