NYSE Composite's market value is the price at which a share of NYSE Composite stock trades on a public exchange. It measures the collective expectations of NYSE Composite investors about the entity's future performance. 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 tightly coupled with the direction of predictive economic indicators such as signals in gross domestic product.
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.
No Change 0.00
In 30 days
If you would invest 0.00 in NYSE Composite on February 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 30 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.
Sophisticated investors, who have witnessed many market ups and downs, frequently view the market will even out over time. This tendency of NYSE Composite's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy. Please use the tools below to analyze the current value of NYSE Composite in the context of predictive analytics.
Please note, it is not enough to conduct a financial or market analysis of a single entity such as NYSE Composite. Your research has to be compared to or analyzed against NYSE Composite's peers to derive any actionable benefits. When done correctly, NYSE Composite's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in NYSE Composite.
NYSE Composite Backtested Returns
NYSE Composite has Sharpe Ratio of 0.25, which conveys that the entity had 0.25% return per unit of standard deviation over the last 3 months. Our standpoint towards estimating the volatility of an index is to use all available market data together with index-specific technical indicators that cannot be diversified away. We have found twenty-four technical indicators for NYSE Composite, which you can use to evaluate the future 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. By reviewing NYSE Compositetechnical indicators, you can currently evaluate if the expected return of 0.16% will be sustainable into the future.
Very good predictability
NYSE Composite has very good predictability. Overlapping area represents the amount of predictability between NYSE Composite time series from 3rd of February 2024 to 18th of February 2024 and 18th of February 2024 to 4th of March 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 0.85 indicates that around 85.0% of current NYSE Composite price fluctuation can be explain by its past prices.
Spearman Rank Test
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 index has exhibited high autocorrelation historically, and you observe that the stock is moving up for the past few days. In that case, you can expect the stock movement to match the lagging time series.
Current and Lagged Values
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
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.
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Check out Correlation Analysis to better understand how to build diversified portfolios. Also, note that the market value of any Index could be tightly coupled with the direction of predictive economic indicators such as signals in gross domestic product. You can also try the Portfolio Holdings module to check your current holdings and cash postion to detemine if your portfolio needs rebalancing.
Complementary Tools for NYSE Index analysis
When running NYSE Composite's price analysis, check to measure NYSE Composite's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy NYSE Composite is operating at the current time. Most of NYSE Composite's value examination focuses on studying past and present price action to predict the probability of NYSE Composite's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move NYSE Composite's price. Additionally, you may evaluate how the addition of NYSE Composite to your portfolios can decrease your overall portfolio volatility.
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NYSE Composite technical index analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, index market cycles, or different charting patterns.
A focus of NYSE Composite technical analysis is to determine if market prices reflect all relevant information impacting that market. A technical analyst looks at the history of NYSE Composite trading pattern rather than external drivers such as economic, fundamental, or social events. It is believed that price action tends to repeat itself due to investors' collective, patterned behavior. Hence technical analysis focuses on identifiable price trends and conditions. More Info...
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