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Stationarity tests in the frequency domain for regression

Strict stationarity is the strongest form of stationarity. It means that the joint statistical distribution of any collection of the time series variates never depends on time. So, the mean, variance ...
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465 views

Oscillatory time-series forecasting

I was wondering if this mean(160)-reverting/oscillatory time series "SUM" can be considered chaotic & forecastable to some extend short-term? ...
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206 views

Modeling asset performance to Bitcoin revenue

I'm attempting to model asset performance to Bitcoin revenue, which is a driving force in the Bitcoin community. Question Is there any model, or research being done that tracks "hashes per second" ...
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2answers
342 views

What stock market indicators to model based on twitter feed? [closed]

We are developing an algorithm that models twitter users and groups of words that may indicate real world events. One application is modelling elections, i.e which party is likely going to win. ...
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1answer
57 views

How can I forecast future correlation?

There are some standard models for forecasting volatility (e.g., GARCH) and for forecasting returns (e.g., factor models). What kind of standard models exist for forecasting future correlation between ...
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3answers
427 views

What Is A Good Success Rate Using Machine Learning For A Beginner?

I know this question will be quickly destroyed and my account summarily banned, but I just have to ask: For a trader using machine-learning algorithms (SVMs, ANNs, GAs, Decision Trees) for ...
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1answer
502 views

Selecting timeframe for time series analysis

In technical analysis, we may use confluence of direction for 3 timeframes to roughly gauge bias of market now. Similarly, if we use time series forecasting methods to predict(say daily data-whether ...
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1answer
89 views

How to forecast bond price with time series

I have the goal of being able to develop a model that can forecast the future prices of european government bond (or other private bonds), particularly from the historical prices and returns of the ...
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1answer
110 views

How to fit a SARIMA + GARCH in R?

I'd like to fit a non stationary time series using a SARIMA + GARCH model. I have not found any package that allow me to fit this model. I'm using rugarch: model=ugarchspec( variance.model = ...
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1answer
25 views

Diebold-Mariano test

I am trying to use the Diebold-Mariano test but it doesnt work for some reason. Here is my code: dm.test(maegarch14,maeegarch14,h=126) where ...
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1answer
42 views

Constant decreasing volatility, GARCH forecasting

I am trying to forecast the volatility using GARCH modelling in R. I fit an ARMA(1,1)-GARCH(1,1) model, but my sigma predictions are constantly decreasing. Anybody know why? ...
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1answer
54 views

Forecasting using GARCH in R

I am using the predict and ugarchforecast functions in R. When I fit my models and try to forecast, I get either only increasing or decreasing values for sigma, does anyone know why? Thank you ...
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27 views

Forecasting bond yields

Do you know any models which can be used for prediction of corporate bonds yields (or goverment bonds yields) when we know forecasts of macroeconomic fundamentals (gdp, fed funds rate, interbank rate, ...