NYSE Composite's market value is the price at which a share of NYSE Composite trades on a public exchange. It measures the collective expectations of NYSE Composite investors about its performance. NYSE Composite is listed at 20272.04 as of the 30th of November 2024, which is a 0.31 percent increase since the beginning of the trading day. The index's lowest day price was 20209.82. With this module, you can estimate the performance of a buy and hold strategy of NYSE Composite and determine expected loss or profit from investing in NYSE Composite over a given investment horizon. Check out Correlation 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
NYSE
NYSE Composite '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 NYSE Composite'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 NYSE Composite.
0.00
06/03/2024
No Change 0.00
0.0
In 5 months and 30 days
11/30/2024
0.00
If you would invest 0.00 in NYSE Composite on June 3, 2024 and sell it all today you would earn a total of 0.00 from holding NYSE Composite or generate 0.0% return on investment in NYSE Composite over 180 days.
NYSE Composite 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 NYSE Composite'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 NYSE Composite upside and downside potential and time the market with a certain degree of confidence.
Today, many novice investors tend to focus exclusively on investment returns with little concern for NYSE Composite's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as NYSE Composite's standard deviation. In reality, there are many statistical measures that can use NYSE Composite historical prices to predict the future NYSE Composite's volatility.
NYSE Composite has Sharpe Ratio of 0.17, which conveys that the entity had a 0.17% return per unit of standard deviation over the last 3 months. We have found twenty-seven technical indicators for NYSE Composite, which you can use to evaluate the volatility of the index. The index secures a Beta (Market Risk) of 0.0, which conveys not very significant fluctuations relative to the market. the returns on MARKET and NYSE Composite are completely uncorrelated.
Auto-correlation
0.76
Good predictability
NYSE Composite has good predictability. Overlapping area represents the amount of predictability between NYSE Composite time series from 3rd of June 2024 to 1st of September 2024 and 1st of September 2024 to 30th 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 NYSE Composite price movement. The serial correlation of 0.76 indicates that around 76.0% of current NYSE Composite price fluctuation can be explain by its past prices.
Correlation Coefficient
0.76
Spearman Rank Test
0.56
Residual Average
0.0
Price Variance
130.8 K
NYSE Composite lagged returns against current returns
Autocorrelation, which is NYSE Composite 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 NYSE Composite's index expected returns. We can calculate the autocorrelation of NYSE Composite returns to help us make a trade decision. For example, suppose you find that NYSE Composite 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
NYSE Composite 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 NYSE Composite index is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if NYSE Composite index is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in NYSE Composite index over time.
Current vs Lagged Prices
Timeline
NYSE Composite Lagged Returns
When evaluating NYSE Composite's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of NYSE Composite index have on its future price. NYSE Composite 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, NYSE Composite autocorrelation shows the relationship between NYSE Composite index current value and its past values and can show if there is a momentum factor associated with investing in NYSE Composite.
Regressed Prices
Timeline
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.