Factor analysis, in which both latent (unobserved) and manifest (observed) variables are continuous, is perhaps the best known.
In latent profile analysis the latent variable (e.g. consumer segments) is categorical and the manifest variables (e.g. responses to rating scales) are continuous.
Latent trait models (e.g. item response theory) are characterized by continuous latent variables and categorical manifest variables (e.g. correct or incorrect answers to test items).
In latent class analysis both latent and observed variables are categorical.
There are also hybrid models which include both continuous and categorical latent and manifest variables.
In some models there is a distinction between dependent and independent variables. Censored, truncated and count variables can also be accommodated.
Any of these models can be multilevel (hierarchical) or longitudinal and can incorporate exogenous variables (covariates).
This popular book is focused on latent class analysis and its longitudinal extension, latent transition analysis. It is well written and covers theoretical and technical issues as well as application.
Factor analysis, in which both latent (unobserved) and manifest (observed) variables are continuous, is perhaps the best known.
In latent profile analysis the latent variable (e.g. consumer segments) is categorical and the manifest variables (e.g. responses to rating scales) are continuous.
Latent trait models (e.g. item response theory) are characterized by continuous latent variables and categorical manifest variables (e.g. correct or incorrect answers to test items).
In latent class analysis both latent and observed variables are categorical.
There are also hybrid models which include both continuous and categorical latent and manifest variables.
In some models there is a distinction between dependent and independent variables. Censored, truncated and count variables can also be accommodated.
Any of these models can be multilevel (hierarchical) or longitudinal and can incorporate exogenous variables (covariates).
This popular book is focused on latent class analysis and its longitudinal extension, latent transition analysis. It is well written and covers theoretical and technical issues as well as application.
The SSE was the first modern stock exchange to open in China, with trading commencing in 1990. It has now grown to become the largest stock exchange in Asia and the third-largest in the world by market capitalization, which stood at RMB 50.6 trillion (US$7.8 trillion) as of September 2021. Stocks (both A-shares and B-shares), bonds, funds, and derivatives are traded on the exchange. The SEE has two trading boards, the Main Board and the Science and Technology Innovation Board, the latter more commonly known as the STAR Market. The Main Board mainly hosts large, well-established Chinese companies and lists both A-shares and B-shares.
Spiking bond yields driving sharp losses in tech stocks
A spike in interest rates since the start of the year has accelerated a rotation out of high-growth technology stocks and into value stocks poised to benefit from a reopening of the economy. The Nasdaq has fallen more than 10% over the past month as the Dow has soared to record highs, with a spike in the 10-year US Treasury yield acting as the main catalyst. It recently surged to a cycle high of more than 1.60% after starting the year below 1%. But according to Jim Paulsen, the Leuthold Group's chief investment strategist, rising interest rates do not represent a long-term threat to the stock market. Paulsen expects the 10-year yield to cross 2% by the end of the year.
A spike in interest rates and its impact on the stock market depends on the economic backdrop, according to Paulsen. Rising interest rates amid a strengthening economy "may prove no challenge at all for stocks," Paulsen said.
