How can I use the Sharpe ratio to compare my various investments in my IRAs & 401k?

The calculation for the Sharpe ratio is the Expected Return - RF% / the underlying stock Standard Deviation. All the following calculations and information are from  ZOONOVA

The above image represents a portfolio called “ZooNova Temp.” If you look at the highlighted column in the Analytics grid you will see the calculations for the Sharpe ratio for each position. If a position does not have a calculated Sharpe ratio there may not be enough historical price data to calculate one. At the top of the column you will see a weighted average of the Sharpe ratio for all the positions. This would not represent a Sharpe ratio for the portfolio, that would have to be calculated using a Covariance Matrix that is calculated from the individual position weights, and their Variance.

You will also see that there are many other statistical calculations that are in the Analytics grid. There is also a Conditional Sharpe ratio calculated using Conditional Value at Risk, or CVaR. The Conditional Sharpe Ratio is defined as the ratio of expected excess return to the expected shortfall. CVaR is used as the denominator in the C-Sharpe calculation whereas the standard Sharpe ratio uses Standard Deviation as the denominator.

Some other definitions to the output for each stock are the following:

Info Ratio

The information ratio (IR) is a ratio of portfolio returns above the returns of a benchmark – usually an index – to the volatility of those returns. The information ratio (IR) measures a portfolio manager's ability to generate excess returns relative to a benchmark but also attempts to identify the consistency of the investor. The higher Info Ratio the better.

Jensen's α

Jensen's Alpha (α), often considered the active return on an investment, gauges the performance of an investment against a market index used as a benchmark, since they are often considered to represent the market’s movement as a whole. The excess returns of a fund relative to the return of a benchmark index is the fund's alpha.

Kurtosis

Kurtosis measures the "tail-heaviness" (as opposed to "peakedness" or "flatness") of a distribution compared against a normal distribution (k = 3). A "low" kurtosis (k < 3) indicates fewer/smaller outliers whereas a "high" kurtosis (k > 3) indicates more/greater. With high kurtosis, one will have "fat" tails, higher frequency of outcomes at the extreme negative and positive ends of the distribution curve.

M2

(a.k.a. M2, M-Squared) In simple words, it measures the returns of an investment portfolio for the amount of risk taken relative to some benchmark portfolio. Popularly known as Modigliani Risk Adjustment Performance Measure or M2, it was developed by Nobel prize winner Franco Modigliani and his grandaughter, Leah Modigliani, in 1997.

Pds Down

How many periods the stock was down.

Pds Up

How many periods the stock was up.

R S&P 500

(a.k.a. Correlation) Correlation is a statistical measurement of the degree to which two securities move in relation to each other: The higher the correlation, the more similarly they behave. A positive correlation means one is likely to move in the same direction as the other; a negative correlation means one is likely to move opposite to the other; a zero correlation means that there is no relationship between the two.

R2 S&P 500

(a.k.a. R2, R-Squared) R-squared is a statistical measure that represents the percentage of a fund or security's movements that can be explained by movements in a benchmark index. For example, an R-squared for a fixed-income security versus the Barclays Aggregate Index identifies the security's proportion of variance that is predictable from the variance of the Barclays Aggregate Index. The same can be applied to an equity security versus the Standard and Poor's 500 or any other relevant index. R squared is measured from 0–1 or 0–100%. A level of 1, or 100%, means a perfect correlation to the benchmark.

Sharpe

The Sharpe Ratio is a measure that indicates the average return minus the risk-free return divided by the standard deviation of return on an investment. The Sharpe Ratio is a measure for calculating risk-adjusted return, and this ratio has become the industry standard for such calculations. The higher the Sharpe Ratio the better.

Skewness

Skewness measures the degree of asymmetry of a distribution around its mean. Positive skewness indicates a distribution with an asymmetric tail extending toward more positive values; negative skewness indicates a distribution with an asymmetric tail extending toward more negative values; zero skewness means the tails are symmetric. Interpreted as downside risk, positive skewness suggests fewer/smaller negative outcomes whereas negative skewness suggest more/greater.

Sortino

The Sortino ratio is the excess return over the risk-free rate divided by the downside semi-variance, and so it measures the return to "bad" volatility. (Volatility caused by negative returns is considered bad or undesirable by an investor, while volatility caused by positive returns is good or acceptable.) A higher Sortino Ratio is better.

Tracking Error

When using an indexing or any other benchmarking strategy, the amount by which the performance of the portfolio differed from that of the benchmark. In reality, no indexing strategy can perfectly match the performance of the index or benchmark, and the tracking error quantifies the degree to which the strategy differed from the index or benchmark.

Treynor

The Treynor ratio, also known as the reward-to-volatility ratio, is a metric for returns that exceed those that might have been gained on a risk-less investment, per each unit of market risk. The Treynor ratio, developed by Jack Treynor, is calculated as follows: (Average Return of a Portfolio – Average Return of the Risk-Free Rate)/Beta of the Portfolio. The higher the Treynor Ratio the better. P&L. This is the return of the stock from the beginning of the year to the present.

VaR

Value At Risk (VaR) is a statistical technique used to measure and quantify the level of financial risk within a firm or investment portfolio over a specific time frame. This metric is most commonly used by investment and commercial banks to determine the extent and occurrence ratio of potential losses in their institutional portfolios. VaR calculations can be applied to specific positions or portfolios as a whole or to measure firm-wide risk exposure. Zoonova calculates historical VAR using 2 years of daily prices and returns both VAR at 95% and 99% level of confidence.

Variance

Variance is used in statistics for probability distribution. Since variance measures the variability (volatility) from an average or mean and volatility is a measure of risk, the variance statistic can help determine the risk an investor might take on when purchasing a specific security. A variance value of zero indicates that all values within a set of numbers are identical; all variances that are non-zero will be positive numbers. A large variance indicates that numbers in the set are far from the mean and each other, while a small variance indicates the opposite.

Variance Neg

The calculated negative variance of the stock over the specified period, 2 years.

Volatility

Standard deviation is a statistical term that measures the amount of variability or dispersion around an average. Standard deviation is also a measure of volatility. Generally speaking, dispersion is the difference between the actual value and the average value. The square root of the variance equals the standard deviation.

Volatility Neg

The negative volatility, or standard deviation, of the stock over the specified period of time.