Questions tagged [forecasting]
The forecasting tag has no usage guidance.
234
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One-step ahead forecast of a AR(1) process (GARCH context)
I am using a Matlab toolbox for obtaining one-step ahead forecasts of the conditional mean from the ARMA(1,0)-GARCH(1,1) process and I have encountered a piece of code that contains, in my opinion, a ...
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Forecast of volatility
What are the well known methods for forecasting (daily - weekly - monthly) volatility of a stock price? How about a bond price?
Let's say I have in my disposition the price time series at a very high ...
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How do I use common forecasting models to forecast FUTURE values? [closed]
I would like to forecast likely future demand based on historical demand. The problem is: I have no mathematical background and in relevant tutorials and even in literature formulas are used, that ...
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ARIMA Forecasting always converges?
I read an article about arima forecasting and i said that before we forecast arima model, its stationarity has to be checked.
If the model is stationary, it is clear that forecasting converges to ...
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Reconciling forecasted growth of components and sum
I'm working with a very basic basic forecast model using Compound Annual Growth Rate and I need to reconcile the forecasts at different levels of detail.
Suppose I have two business lines with ...
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Aggregating growth rates
I'm working on a simple forecast model that uses Cumulative Annual Growth Rate (CAGR) to project future growth, and I've run into an apparent paradox.
The model includes multiple lines of business ...
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0
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Cross-sectional moments
I got a seminar topic named Forecasting risk from cross sectional moments? Could at least someone tell me what should I write about and if there is any paper that I could read. Thank you very much in ...
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How to forecast high-frequency data?
Introduction: I have seen a plenty of articles/books regarding volatility forecasting applied to high frequency data, but none of them were dedicated to forecasting the actual prices (for example bid/...
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Density forecast of a GARCH model
I am currently working on developing a series of density forecasts and I am encountering some problems. I am working on weekly S&P 500 returns and the returns process is described as
$r_{t} = \...
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How to use physics models in Time Series Analysis and Forecasting.
I have been studying methods of Technical Analysis for several years and I am disappointed. I actually do not consider it useful. I have not met anyone who can constantly win in the market using these ...
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Is volatility for the next day forecastable? To any extent?
In a more general way: is there
1) a methodological approach to quantify the correctness of a model that produces a probability distribution for the, say, S&P 500 index return for the next ...
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List of Economic Data for Index Forecast
What econometric symbol list (or tickers) could be used to forecast return of global stock market indexes (S&P500, TSX, CAC40, ...) and their subsectors?
I'm aware of the answer to question:
...
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FORECASTING Model AR(1) in an Autoregressive Form The Pi´s Parameters
Ive been implementing a little exercise to obtain the first 2 forecasting points of an AR(1) process. And i want to have the forecasting ponts using the three forms: Im folowing this pdf http://www.le....
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Forecast of ARMA-GARCH model in R
I managed to forecast a GARCH model yesterday and run a Monte Carlo simulation on R. Nevertheless, I can't do the same with an ARMA-GARCH. I tested 4 different method but without achieving an ARMA-...
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Extracting Signal from Noisy Data
Consider a scenario in which Y_t represents the % change in price and we want to use X_t to predict Y_t. We assume that X_t is information we get before Y_t is revealed.
Suppose that in reality Y_t =...
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Is there a relation between these two forecasting/estimation approaches?
When learning econometrics I have usually seen stuff from the following perspective:
Assume $Y_t = f(X_t) + e_t$, where f is some function of $X_t$ (typically linear). For example, assume $Y_t = X_t *...
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Forecasting problem with Geometric Brownian Motion in Wolfram Mathematica
I'm a full time undergraduate student from Peru, and I'm trying to use the Geometric Brownian Motion example used in the help section from Wolfram Mathematica in order to forecast future stock prices,...
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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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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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GARCH modelling and forecasting
I have a few questions regarding GARCH modelling and forecasting and it would be great if someone could help me. I am modelling the log return of oil spot prices using various GARCH models: GARCH, ...
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Moving window forecasting in Python
I am looking to create some code that will out-of-sample forecast the HAR-RV model.
The model itself is formulated as the following, and the betas are estimated through HAC-OLS or Newey-West.
...
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Is it likely that banks would become clients of algotrading companies? [closed]
Algotrading is growing, while banks don't currently have the HR to continually develop sophisticated algorithms on their own.
Is it likely that banks (and governments) would become clients of ...
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Machine learning to build top 3 price scenarios over n days
I have a time series of closing prices for a given stock. I would like to formulate possible future scenarios for the price.
My intention is not to use these "likely" scenarios to take any position. ...
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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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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:
...
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897
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Can I do a GARCH model to forecast a time series?
I read this paper
https://research.aston.ac.uk/portal/files/240393/AURA_2_unmarked_Energy_demand_and_price_forecasting_using_wavelet_transform_and_adaptive_forecasting_models.pdf
the two authors ...
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How to write a home task report which is part of the interview process for a quant position in a trading firm
I recently appeared in an interview for a quant research post in a trading company. As part of the interview, I was given a home-task to solve in a week. The inerviewer gave me a dataset consisting of ...
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Forecast 3m LIBOR USD. Budget purpose
How can I calculate/budget/find a expectation for the 3 month LIBOR for the next 3monts-4 years?
I am calculating a CF scenario on USD 3month Libor + margin. With swaps and fixed rate this is easy, ...
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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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Non-overlapping ranges of HCNN' observables and of state transition function
In the artcicle Forecasting and Trading the High-Low Range of Stocks and ETFs with Neural Networks HCNN is used for forecasting of nine time-series, namely:
returns of the lows
returns of the highs
...
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Using Technical Indicators for forecasting Financial time series using Machine learning models
Hi I am trying to use financial technical Indicators for forecasting, using machine learning models. The usual approach in time series cross validation is to use a moving window or growing window. ...
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Is there any way to easily estimate and forecast seasonal ARIMA-GARCH model in any software?
I use R to estimate a seasonal ARIMA(8,0,0)(5,0,1)[7] model for the seasonal differences of logs of daily electricity prices:
...
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ARIMA model, cannot get rid of low order ACF spike
I've gone through all the steps to fit a good ARIMA model - I plotted the data, I looked at the ADF tests, I looked at the ACF plot with no AR and MA terms just a constants. I came up with an ARMA(0,1,...
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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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Normalization of Market Data in Time Series Correlation
Suppose we have 2 time series of market data, one for each security and we want to correlate between these 2 securities. My question is
How do we handle gaps of missing data in the time series? ...
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HAR-RV, realized GARCH and HEAVY model for realized volatility
I don't have much experience with volatility modeling using intraday data but I'm in the process of collecting 5mins data. Currently I have ~6 months of data. Is it enough to use these models with ...
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Estimate rolling stochastic volatility forecast using stochvol in R
I want to use the R package stochvol to fit a SV model to a DAX training set and use the output to estimate a rolling one-step-ahead forecast:
...
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How To Account For Inflation Over Historical Data
I believe inflation is greatly affecting my sample data, even when using percent-changes for movements. I have read this post, which recommends the formula ((Current-Base Year CPI) * Price) / (...
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Implementing A 50/50 Prediction Model Strategy
Reworded the question for clarity (see edits for original post):
How can one knowingly foresee where a 50/50 prediction model will be profitable? For previous posts: I understand that if I have a 50/...
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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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2
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Infinite autocorrelation - Unit root?
I have a time series of gold prices, on which I want to build an ARIMA model. The series is autocorrelated and if I can difference as often as I want, it always is.
First:
data: d1gold
Dickey-Fuller ...
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Why are multiple custom curves (swap) built for one desk?
Currently in a journey of learning and getting my hands a bit dirty with Interest Rate Swaps.
Why there are multiple customized curves built by many even within one desk? For e.g. Short Rates desk ...
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How would you correct a GARCH model to deal with non mean reverting volatility?
I am currently attempting to model and forecast volatility of bitcoin but have not been able to find a GARCH model that fits the data appropriately. I've used tick data sampled at 1 hour intervals ...
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To understand FOMC events and its impact on the market
Last month when FOMC meeting decision went out that fed would start to exit QE3, immediately we saw a deleveraging effect: SPY went down, GLD went down, and LQD (bond) went down, but US dollars went ...
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How to estimate real-world probabilities
In the world of finance, Risk-neutral pricing allow us to estimate the fair value of derivatives using the risk free rate as the expected return of the underlyings.
However, the behavior of ...
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Assessing Forecasting with Correlated Residuals
Trying to use a linear regression model to forecast the CPI. I noticed that when I took a moving average of the residuals, though homoscedatisc and nonautocorrelated (i.e. they squiggle up&down ...
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Calculating the probability of a price change using an options pricing formula
I don't know if I'm doing this right and I'd greatly appreciate help.
I'm trying to use an option pricing formula to backout the likelihood of the Euro dropping below $1.27, even for a minute, at any ...
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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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How to calculate two-time scale variance?
I am having trouble understanding how to calculate two-time scale variance as I do not have a strong mathematical background. Suppose I want to calculate the TSRV at 5 min intervals. Do I calculate ...
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The Basis of Using Technical Indicators as Inputs
In the process of my research I very often come across academic papers regarding modelling and trading strategies that in one way or another incorporate some technical indicators. For example in some ...
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