Questions tagged [forecasting]

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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 ...
MilTom's user avatar
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2 votes
1 answer
86 views

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, ...
Pat's user avatar
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3 votes
1 answer
147 views

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 ...
QMath's user avatar
  • 129
0 votes
1 answer
233 views

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. ...
user1414512's user avatar
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0 answers
80 views

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 ...
probablysid's user avatar
0 votes
1 answer
57 views

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 ...
Lejoon's user avatar
  • 147
0 votes
2 answers
140 views

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 ...
Special Sauce's user avatar
0 votes
0 answers
16 views

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!
spacemonkey's user avatar
2 votes
2 answers
229 views

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 ...
deblue's user avatar
  • 281
0 votes
0 answers
83 views

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 ...
Petra Di Mario's user avatar
1 vote
1 answer
416 views

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 ...
Moataz's user avatar
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1 vote
0 answers
37 views

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 ...
savoga's user avatar
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1 vote
0 answers
439 views

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 ...
Sebastien Wdowiak's user avatar
0 votes
1 answer
93 views

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 ...
stevew's user avatar
  • 145
1 vote
2 answers
345 views

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 ...
wlog's user avatar
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3 votes
0 answers
221 views

"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 ...
FooBaz's user avatar
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0 answers
304 views

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, ...
GusC's user avatar
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0 answers
86 views

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 ...
BSel's user avatar
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0 votes
0 answers
60 views

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?
edd's user avatar
  • 223
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0 answers
38 views

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 ...
Dark2018's user avatar
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1 vote
0 answers
99 views

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 ...
Jordan Wrong's user avatar
1 vote
0 answers
70 views

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 ...
P. Howe's user avatar
  • 11
0 votes
0 answers
99 views

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 ...
Mark Fisher's user avatar
1 vote
0 answers
45 views

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. ...
yash agarwal's user avatar
2 votes
0 answers
330 views

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 ...
Kareem Sayed's user avatar
1 vote
0 answers
124 views

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 ...
lara_toff's user avatar
  • 113
0 votes
1 answer
60 views

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 ...
Melly Donald's user avatar
0 votes
0 answers
46 views

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 ...
Sebastian Strauss Hansen's user avatar
11 votes
1 answer
303 views

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,...
sets's user avatar
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1 vote
0 answers
58 views

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, ...
CasusBelli's user avatar
3 votes
1 answer
307 views

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 ...
Hans's user avatar
  • 2,706
1 vote
0 answers
50 views

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 ...
rjdata-analyst's user avatar
-4 votes
1 answer
299 views

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....
PlatinumMaths's user avatar
0 votes
2 answers
155 views

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 ...
user30609's user avatar
  • 133
0 votes
1 answer
124 views

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 ...
Swaraj_r's user avatar
0 votes
0 answers
59 views

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 ...
ken4ward's user avatar
  • 101
2 votes
1 answer
140 views

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 ...
ABK's user avatar
  • 126
-1 votes
1 answer
130 views

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 ...
Jur's user avatar
  • 11
1 vote
0 answers
52 views

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?
Hans's user avatar
  • 2,706
0 votes
1 answer
606 views

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 ...
Luigi87's user avatar
  • 326
0 votes
0 answers
74 views

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 ...
Lester Jack's user avatar
0 votes
3 answers
684 views

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 ...
Vladimir Belik's user avatar
0 votes
1 answer
73 views

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 (...
Jur's user avatar
  • 11
0 votes
0 answers
54 views

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 ...
jitmanchan's user avatar
1 vote
0 answers
116 views

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. ...
s5s's user avatar
  • 452
2 votes
1 answer
766 views

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, ...
Vladimir Belik's user avatar
0 votes
0 answers
108 views

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 ...
develarist's user avatar
  • 2,970
2 votes
2 answers
921 views

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 ...
Kai's user avatar
  • 43
0 votes
0 answers
172 views

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 ...
Matteo's user avatar
  • 63
0 votes
2 answers
1k views

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 ...
Xtiaan's user avatar
  • 103

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