Does anyone know how to do Time Series Regression. I need to learn to do this for my HHS 265 class. Please share with me the steps to this process.

Does anyone knows how to anaylze the WACC, risk and NPV from a given spreadsheet. Thanks

A small company was founded by 2 electronic engineers, Tom and Jessica, 15 years ago. The company manufactures integrated circuits to capitalize on complex mixed-signal design technology and has recently entered the market for frequency timing generators, or silicon timing devices, which provide the timing signal or clocks necessary to synchronize electronic systems. Its clock products originally were used in PC video graphic applications, but the market subsequently expanded to include motherboards, PC PERIPHERAL DEVICES, AND OTHER digital consumer electronics, such as digital television boxes and game consoles. The company design and markets custom application-specific integrated circuits (ASICs) for industrial customers. The ASIC'S design combines analog and digital, or mixed-signal, technology. In addition to the two founders, Nolan Pittman, who provided capital for the company is the 3rd owner. Each owns 25 percent of the 1 million shares outstanding. Several other individuals, including current employees, own the remaining company shares.

Recently, the company designed a new computer motherboard. The company's design is both more efficient and less expensive to manufacture, and the ETI design is expected to become standard in many personal computers. After investigating the possibility of manufacturing the new motherboard, the company determine that the costs involved in building a new plant would be prohibitive. The owners also decided that they were unwilling to bring in another large outside owner. Instead, the company sold the design to an outside firm. The sale of the motherboard design was completed for an aftertax payment of $30 million.

Question - Jessica believes that the company should use the extra cash to pay off debt and upgrade and expand its existing manufacturing capability. How would Jessica's proposals affect the company?

The third owner is in favor of a share repurchase. HE Argues that a repurchase will increase the company's P/E ratio, return on assets, and return on equity. Are his arguments correct? How will a share repurchase affect the value of the company?

Of course! I'd be happy to explain the process of conducting time series regression. Here are the steps you can follow:

Step 1: Understand Time Series Regression
Before diving into the process, it's important to understand the concept of time series regression. Time series regression is a statistical technique used to analyze the relationship between a dependent variable and one or more independent variables over time. It is commonly used in fields such as economics, finance, and forecasting.

Step 2: Gather Data
The first step is to locate and gather the necessary data for your analysis. Time series data consists of observations recorded at different time points. Ensure that you have a sufficient number of observations to capture the underlying patterns and trends.

Step 3: Visualize the Data
Visualizing the data is crucial to gain insights and identify any apparent patterns or trends. Plotting the time series data as a line graph or using other visualization techniques can help you understand the behavior of the variables over time.

Step 4: Model Selection
Choose an appropriate time series regression model that suits your data and research question. Some common models include autoregressive integrated moving average (ARIMA), autoregressive conditional heteroscedasticity (ARCH), and vector autoregression (VAR), among others. The model selection depends on the nature of your data and the purpose of your analysis.

Step 5: Preprocess the Data
Data preprocessing may be required to ensure that your data meets the assumptions of the chosen model. This step may involve handling missing values, transforming the data to stabilize variance, differencing to achieve stationarity, or other necessary adjustments.

Step 6: Estimate the Regression Model
Fit the selected time series regression model to your data. The estimation process varies based on the chosen model. For instance, if you are using ARIMA, you will need to estimate the model parameters through techniques like maximum likelihood estimation.

Step 7: Evaluate the Model
Assess the goodness of fit of your estimated model to evaluate its performance. Various diagnostic tests, such as residual analysis, can help determine if the model adequately captures the underlying relationships in the data.

Step 8: Interpret the Results
Once you have a satisfactory model, interpret the estimated coefficients and their significance. Analyze the effects of the independent variables on the dependent variable over time. Interpretation will depend on the specific context and research question.

Step 9: Make Forecasts and Evaluate Performance
One of the benefits of time series regression is its ability to make future predictions. Utilize your estimated model to make forecasts of the dependent variable for future time points. Then assess the performance of your model's forecasting accuracy using appropriate measures, such as mean squared error or mean absolute error.

Remember, these steps provide a general guideline for time series regression. The details and complexity may vary depending on the specific techniques and software you choose to employ. Also, consulting textbooks or online resources dedicated to time series analysis can provide a deeper understanding of the subject.