Questions tagged [forecasting]
The forecasting tag has no usage guidance.
233
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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 ...
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Recommended books/resources for IRRBB risk metrics calculation
Any recommendations for books/resources/videos/on-demand courses for in-depth IRRBB-related risk metrics calculation etc?
Yield Curve Risk, Basis Risk, Repricing Risk, Optionality Risk, Value at Risk, ...
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Effect of back-transforming forecasted mean of log returns to get forecasted mean of price
When trying to forecast time series, say forecasting the level of a stock index so we can forecast the future values of an option, it tends to be helpful to analyze the log returns versus the original ...
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Is a volatility forecast essentially a delta forecast in vanilla European options?
As the title suggests.
I want to understand why delta hedging is done. I'd like to illustrate with an example:
Say you have 7 dte option chain with 15.8% IV ATM straddle on an underlying of spot 100.
...
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Is my time horizon for GARCH(1,1)/ARCH(1)/EGARCH(1,1) reasonable?
I am trying to learn about volatility forecasting using three models: ARCH(1), GARCH(1, 1) and EGARCH(1, 1) using python. I wanted to know if my general procedure is correct, and specifically if my ...
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Optimal Input and Target Variables for Forecasting Using a Deep Neural Network on Daily Stock/Index Data [closed]
What is the optimal input and target variables for forecasting with a deep neural network on daily stock/index data? More specifically I’m training a temporal convolutional network, but a more general ...
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142
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Appropriate way to combine alternative volatility estimates
I have a number of different annualized realized volatility estimates (for the same point in time) that I'd like to combine. Is a simple average over these appropriate? Or should I do this in the ...
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Historic EPS forecasts for S&P500 [duplicate]
Looking for a free dataset of earnings forecasts for S&P500. It would be interesting to plot the accuracy of forecasts vs the actual.
Cheers!
- 153
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2
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230
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Assessing the GARCH model out-of-time
I have fitted two competing GARCH models, one GARCH(1,2) model and another EGARCH(1,1,1) both with t-distributed errors, on the ...
- 281
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86
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Move from risk-neutral probability to historical probability
I am working on a density forecasting project using options. Using the Breeden-Litzenberger formula it is possible to find the implied density at maturity under the risk neutral probability of an ...
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1
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418
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Multistep ahead forecasts in GARCH equations
If my one step ahead forecasts from GARCH(1,1)-X are:
\begin{equation}
\hat{h}_{t+1} = \hat{\alpha}_0 + \hat{\alpha}_1 \hat{u}^2_t + \hat{\beta}_1 \hat{h}_t + \hat{\psi} X_t
\end{equation}
Where ...
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Inflation in wealth forecast [closed]
I am building a model to simulate people's wealth in the next years.
Say Mr X has a portfolio with an expected return of 3% (annual). From this I can simulate the return of his portfolio in the next ...
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450
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How to forecast volatility using gamma exposure index?
Brainstorming this afternoon.
GEX is the gamma exposure index (https://squeezemetrics.com/monitor/static/guide.pdf). It's the sum of gamma exposure for call and put.
Using IV, strike and BDS you can ...
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93
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Is intra-forecast-horizon rebalancing suboptimal?
Suppose that I have forward 1-month forecasts of returns that are updated daily. Is it suboptimal to rebalance more frequently than 1-month (e.g., daily or weekly)? Theoretically, if I forecast the ...
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345
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Volatility forecast for 5-minute frequency data
I have high frequency data for financial stocks (5-minute periodicity) and I want to forecast volatility.
I'm familiarized with the usual ARCH/GARCH models and their variants for daily data but after ...
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"Better" forecasts lead to worse asset allocation performance
Short version
If you're trying to produce an asset allocation system, it feels pretty natural to split it into an estimation component that forecasts asset means and covariance, and a weighting ...
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306
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Forecasting VIX with GARCH(1,1)
Aim: Forecast VIX using GARCH(1,1)
Reason: I want to be able to forecast VIX on several horizons, in order to be able to forecast the SP500 index through linear regression.
Tools used: Python, ...
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86
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Good performance of naive forecasting in efficient markets
I am doing spot price forecasting for a market, and so far, the naive forecasting model, which forecasts with the last observed prices, is the best forecasting model. I know that it might be because ...
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60
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How to calculate the term structure of an index that doesn’t have futures
I would like to calculate the term structure of the VVIX index.
Only way I have found so far is forecasting historical prices N months out.
Any other idea?
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Suggestion on the models to estimate public indeces future returns
I would like to to estimate the future returns of some public indeces. I have several of them so it is a multivariate problem.
The series are quarterly and the estimation should be of at least 15-20 ...
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On a relative level how do you value single name volatility? [closed]
Let's say I am looking to price AAPL 30 day volatility on a relative level.
My first thought would be to take SPY vols and multiply it by AAPL's beta.
But this leaves out the volatility caused by the ...
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70
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Building multivariate model to predict trading volumes
I am building a multivariate statistical model to forecast the trading volume of the S&P 500 stock based on its previous values and on other covariates. Being new to finance, I am having problems ...
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99
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Good (non-random walk) financial time series to perform forecasting on
I would like to start with a brief caveat, namely that I am by no means a domain expert in financial markets. Therefore the question I am asking may sound silly to a practitioner but I am asking it ...
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45
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Presence of underestimation bias in consensus earnings predictions
I am working on a financial data that entails forecasted revenue a company generates over a fiscal quarter and the actual revenue for that quarter.
...
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335
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Are there any public implementations of realized kernels? (preferably in Python)
looking to implement a realized kernel model to forecast realized variance of around ~140 equities and indices in Python given order book data.
I have read "Realised Kernels in Practice: Trades ...
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124
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Trying to recreate results from a research paper on HMM and Kolmogorov-Smirnov Test for forecasting regime switching on SP500
I am trying to recreate this research: Regime-Switching Factor Investing with Hidden Markov Models,
by Matthew Wang, Yi-Hong Lin and Ilya Mikhelson
https://www.mdpi.com/1911-8074/13/12/311/htm
My ...
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60
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How to create a local price index?
I have a set of real estate data; historic sales price, square meters, location (latitude, longitude), neighbourhood, city, sold date and bunch of other features. I have used a boosting model to ...
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46
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Perfect in-sample size for out-sampling volatility prediction (EGARCH(1,1)
I have a few questions regarding in-sample size for volatility forecasting in EGARCH(1,1). I'm currently sitting with a dataset consisting of 1387 trading days of the S&P-500 index. I would like ...
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303
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Trading strategy for a misspecified density
I am trying to implement a strategy that exploits potential misspecifications in density predictions (e.g.: long states with too-low probability; short states with too-high probability).
In particular,...
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Price Prediction Intervals from Forecasted Returns (ARIMA)
I have successfully fit an ARIMA model to a time series of the daily returns of power futures prices. The question I have is: How can I create a prediction interval for the prices? Or, alternatively, ...
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307
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Is there a HAR that deals with the leverage effect?
The EGARCH is a special GARCH model that treats the leverage effect of the volatility. The HARV does not make a distinction between negative and positive returns. Is there a special HARV that deals ...
- 2,706
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How do I deal with nonexistant data in a time series with an irregular frequency?
I am trying to do some time series analysis on the margin resulting from three specific commodity futures contracts and ultimately forecast the margin. The margin is calculated as M = F1 + F2 - F3. I ...
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299
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Using geometric brownian motion for stock price forecasting [closed]
I am doing a dissertation in finance on a maths degree. I wanted to forecast stock prices using artifcial neural networks but none of my tutors are able to supervise so I'm having to do something else....
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155
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Forecasts for the S&P 500?
Would anyone know of any monthly forecasts for the S&P 500, historical over a long time periods.
Websites like estimize provide forecasts of all sorts of things likes stocks and the balance of ...
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124
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How do you simulate returns for a portfolio when you have Lumpsum + Monthly investments (SIP) in place?
I'm trying to simulate portfolio returns using Norm.inv function in excel.
Inputs to the formula: Prob= Rand, Std dev= Historical, Mean= 5 year historical average.
Its easy to do this when you're ...
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60
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Fitting a Spread into ARIMA AR(1) process
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 ...
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forecasting hourly variance with higher resolution data available
Assume one has price data $P_{1}, P_{2}, \dots, P_{n}$ with one hour resolution and aims to forecast the variance for one hour ahead return. The first approach to try is ARCH or GARCH models. There ...
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Why is Banque de France using BVAR with different orders of integration?
Don't all the variables used have to be of the same order of integration in VAR models ?
In this paper Bayesian VAR Forecasts, Survey Information and Structural Change in the Euro Area Gergely Ganics ...
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Volatility forecast on SPX option expiration day
I am looking for methods and papers on forecasting SPX option at-the-money implied volatility or realized volatility within its expiration day. What are some stylized facts and forecasting methods?
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608
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Use of ugarchroll vs ugarchforecast: setting parameters
I would like to generate 21 day ahead forecast volatility with ugarchroll.
I know it is similar to ugarchforecast with the exception that ugarchroll is a rolling average which considers initially the ...
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74
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Optimal trading given frequently delivered directional forecast
I am interest in trading by optimally exploiting a directional forecast given by an oracle.
The oracle predicts directionally the price of an asset (higher or lower than at the moment of forecast ...
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3
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685
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Consistent offset/lag in time-series prediction using Neural Network (all code provided)
I'm using a neural network (keras package) to predict Bitcoin prices 48 hours in advance. The issue is that for some reason, my predictions are "correct" but they are lagging behind the true ...
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Is it legitimate to assess the resilience of industries and sectors through the stock market?
I would like to assess the resilience of some sectors in Europe but I honestly lack data, and it seemed to me the simplest solution to be able to implement univariate (arima etc) and multivariate (...
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Excess Daily Returns to Excess Quarterly Returns
I am building a model which predicts the Excess Daily Returns over a time period. How do I convert these excess daily returns to excess quarterly returns? Should I just do an average of all the daily ...
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Modelling volatility for higher frequency data
I'm doing some academic work on volatility forecasting. I've got 1-minute bar data. It is not clear to me what model is best suited for forecasting volatility when higher frequency data is available.
...
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Why are my Neural Network predictions “correct”, but offset from true value? Not using any past lagged values
Please bear with me through the whole question - I just want to make it very clear what I've done so far and why I'm so perplexed.
I am working with a neural network with the Keras package in R, ...
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108
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Is non-linear correlation problematic in financial time series prediction?
Many traditional finance models assume linear relationships between variables and features. Aren't linear correlations/covariances unable to capture financial processes empirically since they actually ...
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922
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How does Linear-Exponential Loss (Linex) function tend towards Quadratic Loss function?
Thank you for your help everyone, and I apologise beforehand if this is a lousy or dumb question.
I am looking to read up more on Quadratic Loss & Linex Loss, and forecast optimality.
In my ...
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172
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Optimal predictors for 1-month returns
I am implementing a Random Forest classifier algorithm on Python for predicting future stock returns (one month). My goal is to foresee whether the cumulative returns in a month will be negative or ...
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How to obtain one-step ahead forecast in Python based on GARCH?
I am trying to produce one-step ahead forecast using GARCH in Python using a fixed windows method. I ultimately want to put the code below in a for loop, but this code snippet does not perform as I ...
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