# Questions tagged [forecasting]

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### Target Realized Volatility or Realized Variance in Forecasting

There are many academic paper doing volatility forecasts using realised variance and realised volatility interchangeably -- both targeting the proxy estimation of sum of squared returns (realized ...
1 vote
51 views

### Excess Return Evaluation Bias

Im currently working on a Alpha and Risk Model for constructing portfolios. From what Ive read on books and here, they are constructed in a different way and produce differents results. My Risk Model (...
67 views

### Cross-day realized volatility

I've been looking for papers on volatility forecast, and most of them focus either on daily volatility (often using daily returns to access predictions for monthly volatility). Others focus on ...
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1 vote
80 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 ...
19 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
95 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
66 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
96 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 ...
• 468
83 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 ...
35 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 ...
85 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
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
76 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, ...
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 ...
1 vote
328 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
163 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
113 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
92 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
154 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, ...
• 21
289 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 ...
• 249
1 vote
335 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. ...
226 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 ...
69 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 ...
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248 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 ...
490 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 ...
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116 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 ...
1 vote
954 views

### Multistep ahead forecasts in GARCH equations

If my one step ahead forecasts from GARCH(1,1)-X are: $$\hat{h}_{t+1} = \hat{\alpha}_0 + \hat{\alpha}_1 \hat{u}^2_t + \hat{\beta}_1 \hat{h}_t + \hat{\psi} X_t$$ Where ...
• 43
1 vote
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 ...
• 11
1 vote
886 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 ...
138 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 ...
• 145
1 vote
609 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 ...
• 11
228 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 ...
• 31
431 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, ...
• 1
90 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 ...
• 1
74 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?
• 223
39 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 ...
• 101
1 vote
126 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 ...
• 181
1 vote
80 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 ...
• 11
118 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 ...
1 vote
47 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. ...
463 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 ...
1 vote
166 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 ...
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63 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 ...
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 ...
318 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,...
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1 vote
70 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, ...
• 555
411 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 ...
• 2,806
1 vote
52 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 ...