1. K

    Fitting a spread into ARIMA AR(1)

    I'm a newbie to econometrics. I've simply ran a regression and have coefficient values of the variables. I'm running a regression for a crypto data, and I've gotten the Spread of the variables. To forecast, I'll need to fit this spread into ARIMA AR(1) process after finding the best fit is...
  2. J

    ARIMA model forecasting

    I am having difficulty answering this question, would appreciate any help provided, thanks.
  3. B

    How to continue raw data for Forcasting ~ Holts-Winter

    Hi All, I am new to this forum and i am in need of help regarding the Holt's Winter Method. I've managed to build a forecasting model in excel using the Damped method which works very well. But due to my lack of experience, I am confused on how to continue the raw data as the forecasting...
  4. A

    General questions related to statistics

    1. why is return forecasting (eg forecasting stock return) important in general? 2. How can we calculate Dividend price ratio from return index and price index? to change the independent variables to have one-sided alternative in in-sample regression? 4. what is Principal component...
  5. M

    time series analysis

    There is an aggregated measure represented by a variable A, modeled as a time series from a process. There was a need forecast A and also to find out the historical amount of data of A that is the best reflector of future values of A (as there was a data storage capacity issue). Using a...
  6. M


    There is an aggregated measure represented by a variable A, modeled as a time series from a process. There was a need forecast A and also to find out the historical amount of data of A that is the best reflector of future values of A (as there was a data storage capacity issue). Using a...
  7. S

    Forecasting with autocorrelation present

    Hello, if one is to compare different lag orders for forecasting (and minimize RMSFE, root mean squared forecast error) for lets say autoregressive models and the datagenerating process is an AR(4) model. Thereby using an AR(3) model to forecast one should expect worse RMSFE values than an AR(4)...
  8. E

    Forecasting/Future prediction assistance

    Hi guys, I've got a bit of advertising data here and I'd like to make a model out of it which can predict future events. So I have the amount of money spent, the number of billboards we've got and how many people we think have seen the billboard. We also have the number of walk ins we...
  9. J

    Newbie HR guy - how to best forecast retirements in company

    Hi - I am a HR professional looking to self learn statistical modeling for new responsibilities at work..Need to forecast no. of employees who may retire next 10 years. What would be simple way to forecast for this? I have historical retirements data broken by age groups (50-55 etc). Have...
  10. S

    Regression analysis with sales forecasting

    Hello, I am in the process of using a regression model to help predict the forecast of soft drinks. I have 52 sets of weekly data and my independent variables are feature space, temperature, price, competitor price and competitor feature space after having omitted some predictor variables due...
  11. S

    Regression and seasonality

    I am running a multiple linear regression analysis to show how different demand factors affect demand of juice. My independent variables are price, temperature, competitor price, feature space and competitor feature space. However, I know there is an element of seasonality which is affecting the...
  12. J

    MA() part of ARIMA: How do you get error terms?

    I've been through the excellent forecasting book coauthored by Hyndman on I'm having trouble understanding the actual algorithm. The MA(x) is supposed to be a moving average of error terms. But where does the error come from? Is it based on the AR(x) term? In that case, what about...
  13. P

    GARCH modelling and forecasting

    Hi, I have a few questions regarding GARCH modelling and forecasting and it would be great if someone could help me. I am modelling oil spot prices log-return using various GARCH models: GARCH, APARCH, EGARCH... and I am trying to forecast the prices. I found using ACF and PACF plots that the...
  14. T

    Selection of forecasting method - Winter/ARIMA/TBATS in R

    Please find my dataset and forecast outputs attached. A) First sheet contains March-2011 to February 2014 data and forecast for March-2014 to February 2015 using ARIMA,Winter's,TBATS and BATS method.It also has forecast errors obtained by comparing with actual output. B) Second sheet has...
  15. T

    How to find correlation coefficients for periodic data?

    Please help: Correlation coefficients for periodic data? I am working on a hedging model for commodity.I have past 36 months data of commodity market price and future contracts price. e.g. on 1st April,2014, market price is x,April contract price = x+1,May contract price = x+2 and June...
  16. T

    Price forecasting model

    I am working on a problem where I have an item 'x' which is available in local market and 'x' is produced using item 'y'.Item 'y' is traded in futures market.I have historic price data available for last 2 years of both items. I have to forecast prices of x for next year. What should be my...
  17. R

    Reading/converting time series in R

    Hi, I am relatively new to R and struggling with a probably trivial task. My challenge: I want to forecast hourly Power prices. And this is already where the dilemma starts as I am not sure how to tackle this best. Since there is an obvious weekly cycle (ie Power Prices much lower on weekends)...
  18. R

    Using survival analysis to predict scope of truncated data

    I'm not sure I'm thinking about this correctly, and would be grateful for any insight as I think the problem is analogous to one that comes up in biostatistics. I have data on payment to attorneys for representing clients (at public expense). I only learn about the existence of the...
  19. C

    ARMA one step ahead forecast and forecast error

    For a ARMA(1,1) process with constant \theta is X_t=\alpha X_{t-1}+\theta +Z_t+\beta Z_{t-1} where Z_T is white noise with mean 0 and variance\sigma ^2. 1)Find the one step ahead forecast 2)Find the expected value and variance of one step ahead forecast error Here's what I did...
  20. S

    Forecasting with fewer data points

    Hi, Can someone provide more insights on how we can achieve forecasting with fewer data points and come up with more accurate models. I have tried regression however MAD is at 18% and is too high for my model. Thanks!