# DAX Index (Germany) Market Value

GDAXI Index | 19,256 108.42 0.57% |

**19256.27**as of the 6th of November 2024. This is a

**0.57% up**since the beginning of the trading day. The index's open price was

**19147.85**. With this module, you can estimate the performance of a buy and hold strategy of DAX Index and determine expected loss or profit from investing in DAX Index over a given investment horizon. Check out Risk vs Return Analysis to better understand how to build diversified portfolios. Also, note that the market value of any index could be closely tied with the direction of predictive economic indicators such as signals in gross domestic product.

Symbol | DAX |

## DAX Index 'What if' Analysis

In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to DAX Index's index what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of DAX Index.

11/17/2022 |
| 11/06/2024 |

If you would invest

**0.00**in DAX Index on**November 17, 2022**and sell it all today you would**earn a total of 0.00**from holding DAX Index or generate**0.0%**return on investment in DAX Index over**720**days.## DAX Index Upside/Downside Indicators

Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure DAX Index's index current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess DAX Index upside and downside potential and time the market with a certain degree of confidence.

Downside Deviation | 0.6883 | |||

Information Ratio | 0.0358 | |||

Maximum Drawdown | 3.15 | |||

Value At Risk | (1.00) | |||

Potential Upside | 1.5 |

## DAX Index Market Risk Indicators

Today, many novice investors tend to focus exclusively on investment returns with little concern for DAX Index's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as DAX Index's standard deviation. In reality, there are many statistical measures that can use DAX Index historical prices to predict the future DAX Index's volatility.Risk Adjusted Performance | 0.1471 | |||

Total Risk Alpha | 0.0143 | |||

Sortino Ratio | 0.0381 |

## DAX Index Backtested Returns

DAX Index secures Sharpe Ratio (or Efficiency) of 0.19, which denotes the index had a 0.19% return per unit of volatility over the last 3 months. We have found twenty-five technical indicators for DAX Index, which you can use to evaluate the volatility of the entity. The entity shows a Beta (market volatility) of

**0.0**, which means not very significant fluctuations relative to the market. the returns on MARKET and DAX Index are completely uncorrelated.## Auto-correlation | 0.55 |

### Modest predictability

DAX Index has modest predictability. Overlapping area represents the amount of predictability between DAX Index time series from 17th of November 2022 to 12th of November 2023 and 12th of November 2023 to 6th of November 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of DAX Index price movement. The serial correlation of

**0.55**indicates that about 55.0% of current DAX Index price fluctuation can be explain by its past prices.Correlation Coefficient | 0.55 | |

Spearman Rank Test | 0.37 | |

Residual Average | 0.0 | |

Price Variance | 929.9 K |

## DAX Index lagged returns against current returns

Autocorrelation, which is DAX Index index's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting DAX Index's index expected returns. We can calculate the autocorrelation of DAX Index returns to help us make a trade decision. For example, suppose you find that DAX Index has exhibited high autocorrelation historically, and you observe that the index is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.

Current and Lagged Values |

Timeline |

## DAX Index regressed lagged prices vs. current prices

Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If DAX Index index is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if DAX Index index is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in DAX Index index over time.

Current vs Lagged Prices |

Timeline |

## DAX Index Lagged Returns

When evaluating DAX Index's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of DAX Index index have on its future price. DAX Index autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, DAX Index autocorrelation shows the relationship between DAX Index index current value and its past values and can show if there is a momentum factor associated with investing in DAX Index.

Regressed Prices |

Timeline |