APT Crypto | | | USD 6.86 0.55 7.42% |

Aptos information-ratio technical analysis lookup allows you to check this and other technical indicators for Aptos or any other equities. You can select from a set of available technical indicators by clicking on the link to the right. Please note, not all equities are covered by this module due to inconsistencies in global equity categorizations and data normalization technicques. Please check also

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Aptos has current Information Ratio of 0.07. The Information Ratio is the ratio of the alpha component of total returns to the standard deviation of these excess alpha returns. The alpha component is the return that is attributable to the manager skill to time the market and is the residual after taking out the risk-free return and the beta components from the total returns. While the Sharpe ratio considers the standard deviation of the total returns, the information ratio considers the variability of only the alpha component of the return (which also forms the numerator). In other words, the information ratio is merely Jensen alpha divided by its standard deviation.

INFOR | **=** | ER[a] - ER[b] STD[a] |
| = | 0.07 | |

## Aptos Information Ratio Peers Comparison

## Aptos Information Ratio Relative To Other Indicators

Aptos cannot be rated in Information Ratio category at this point. It cannot be rated in Maximum Drawdown category at this point. reporting about

298.06 of Maximum Drawdown per Information Ratio. The ratio of Maximum Drawdown to Information Ratio for Aptos is roughly

298.06 The higher the information ratio, the greater the chances of the manager to make money in the future. The information ratio only looks to compute the return per unit of risk undertaken for the alpha component. This is important because alpha returns are risky, as they represent a zero-sum game for the market as a whole. In fact, the average alpha for the market as a whole is in practice slightly less than zero because of the transaction and other costs. Therefore, it is easy for a manager to take on alpha risk and lose money that will bite into the beta returns.

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