Questions tagged [forecasting]
The forecasting tag has no usage guidance.
246
questions
1
vote
1
answer
74
views
What Quantitative Methods Best Predict Silver Prices Based on Macroeconomic Indicators?
I'm seeking guidance on developing a robust quantitative model to predict silver prices using macroeconomic indicators. How can I incorporate variables like GDP growth, inflation rates, and monetary ...
- 21
0
votes
0
answers
18
views
Time-varying Normal copulas, generating residulas with parameters
I am working with time-varying normal copulas who equation is given by
The dynamic equation of dependence parameter $\rho$ is :
Where
$u_1=F_1 (ε_{1,t} )$ and $u_2=F_2 (ε_{2,t} ) $
I ...
- 23
0
votes
0
answers
73
views
GARCH-MIDAS model for forecasting volatility?
I had a problem when I just estimated the GARCH-MIDAS model on Eviews: I found only the MIDAS model. Can I estimate the GARCH(1,1) model and MIDAS separately, and then multiply them to have GARCH-...
- 1
0
votes
1
answer
63
views
Profitability on Value at Risk forecasting
I'm conducting a research related to Value at Risk forecasting using volatility models like GARCH and others. My predictions are turning out quite well with some models. Is there a way to capitalize ...
1
vote
0
answers
93
views
What are best models to predict mean-reverting processes?
Surprisingly to me, I could not find any paper in the literature that discusses methods to predict a mean-reverting process. What are the best models to predict mean-reverting processes? Would also ...
- 438
0
votes
1
answer
81
views
Predictive Forecast (Close, 14)
I've been following an asset wherein a "R-squared predictive forecast (close, 14)" is posted online each day. On some days, this figure is extremely high, like .92.
Exactly what is the ...
- 1
0
votes
0
answers
34
views
Variance decomposition in the frequency domain
I have done a time-domain decomposition of a generalized forecast error variance from a VAR model of exchange rates and inflation rates. The data are monthly. I am not very adept at doing the ...
- 11
0
votes
0
answers
82
views
What are state-of-the-art methods for forecasting of rates and volatilities?
Usually forecasting is based on a model for the evolution of a value $x(t)$ based on some parameters ${\beta}$ that can then be estimated using various statistical means.
For yield curves and ...
- 141
0
votes
0
answers
48
views
Macro-economic model to predict Copper Prices
I'm currently developing a model based on the current macroeconomic scenario in the world to predict the price of copper 1, 2 and 3 months ahead. That's my idea and I'd like to know what are your ...
- 101
0
votes
0
answers
69
views
Boosting models for algo trading
I’m currently working on a xgboost model to predict the price change above or below a given percentage between a candle’s open price and the next candle’s close price. I use a wide range of features, ...
0
votes
1
answer
76
views
How should I create a Risk measurement Variable?
I have clients who take loans (Advances) weekly. The way that they repay the advance is after 3 weeks when their goods are sold, using the sales proceeds of the goods. But if the goods don't sell for ...
- 11
1
vote
2
answers
303
views
Return forecasting for portfolio optimization
I have some questions related to forecasting returns and how it's used to generate the inputs for portfolio optimization.
First, I want to understand why factor models such as FF- 3-factor model are ...
- 45
1
vote
0
answers
148
views
Portfolio construction in the real world [closed]
Good day. I am looking to understand how the portfolio construction process is actually done in the industry. Now, I do not know if there are too many resources on how things are currently being done (...
- 45
0
votes
0
answers
98
views
Backtesting on factor model residual returns
I've heard in quantitative equity strategies, people backtest signals on residual returns. How does this work in practice? Do people find signals that forecast residual returns and then run the full ...
- 500
0
votes
0
answers
88
views
Forecasting forward curve using Gaussian Process Regression
I have daily closing prices of crude oil monthly contracts up to 36 months. Some contracts are not very liquid so there are missing prices at random. I stitched together contracts to make them rolling ...
- 165