Questions tagged [forecasting]

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60 views

Understanding GARCH

I asked this on stats.stackexchange but I realized this might be a better place to ask this question. I am new to finance and volatility forecasting and am trying to understand how garch model works. ...
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1answer
242 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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26 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, ...
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1answer
72 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 ...
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40 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 ...
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1answer
116 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....
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2answers
143 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 ...
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1answer
92 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 ...
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47 views

Price volatility short-term (10 seconds) forecast

Dataset: list of all realized trades (BTCUSDT) from a certain cryptoexchange with timestamps (15 days worth of data) Problem: predict the "price volatility" (standard deviation of realized ...
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34 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 ...
2
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1answer
74 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 ...
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1answer
115 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 ...
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34 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?
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1answer
97 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 ...
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3answers
172 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 ...
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1answer
69 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 (...
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31 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 ...
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0answers
60 views

Predicting Stock Returns vs Stock Price and then computing returns

I am working on building a model to predict the beta-adjusted returns of a stock using a set of features. At the moment, when I try to predict the stock price directly, instead of the returns, the ...
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0answers
58 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. ...
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1answer
187 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, ...
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59 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 ...
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1answer
163 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 ...
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1answer
377 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 ...
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1answer
135 views

What are some good models for stock price predictions?

For the fitting and forecasting of time-series data on stock price, the most frequent model I have heard of is ARIMA. ARIMA is actually conducting a regression of stock prices and residuals of stock ...
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0answers
56 views

Why are cashflows “modelled backwards in time”?

A am currently reading a manual on how to use some actuarial modelling software to project the expected liability payments made under an annuity contract. In this guide, the following statement is ...
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1answer
36 views

How do you build a model with uncertain time range?

Let's say you want to test the hypothesis that given a signal reaches some threshold, some asset will have some return over the next period. Here we have two unknowns. One, the value of your ...
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1answer
67 views

$n$-day ahead forecast for asymmetric DCC-GARCH model

I am working on forecasting covariances with the use of MGARCH models. I was wondering if anyone knows how to implement a n-day ahead forecast of the aDCC (asymmetric DCC) model in R. The ...
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0answers
27 views

Forecasting accuracy in one month and hedging

I am working on predicting the daily data of a financial time series $[Y(t+1),...Y(t+j)]$ =$f(X_1(t),...X_1(t-i),.....,X_n(t),...X_n(t-i))$ where $Y$ is a commodity price $X_i$ are predictor variables ...
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2answers
282 views

Forecasting volatility farther ahead with autoregressive machine learning

ARIMA and GARCH are old news for predicting volatility time series of asset returns. I am aware of papers that replace ARIMA and GARCH with machine learning algorithms to predict financial volatility ...
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2answers
184 views

How would you forecast volatility without using any programming languages or machine learning or anything of that sort?

I am trying to forecast volatility. I am on the tactical asset allocation team. No one on our team knows machine learning or any programming languages. We are fundamental equity research analysts ...
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1answer
1k views

Find out the effective monthly discount rate for a 10% annual discount rate

First time posting. Apologies in advance if this is not the right question for this forum. If it is, please let me know if I should reformat this in a particular way. If it isn't, would it be more ...
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1answer
42 views

Subscription Based Revenue Prediction

My dataset is on revenues from subscription-based (no commitment, can cancel any time). We have people signing up every year, continue paying for a few years and then gradually cancel the subscription....
3
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1answer
109 views

Predicting natural gas prices using weather data

I developed a model for predicting temperatures and I am planning to add this to a natural gas fair value model together with other parameters. My question is: is the natural gas future price ...
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0answers
195 views

Excel formula for Laplace distribution

I am trying to create a forecast model, projecting the number of passengers through an airport over a period of time (daily, weekly, and monthly). I've already used Excel's FORECAST and POISSON ...
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0answers
85 views

Can variance change over time?

I'm working on a toy project that involves fantasy basketball, I know this is the quantitative finance stackexchange, but it seemed like the best place to ask this question. My goal is to make ...
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2answers
839 views

Can someone explain rigorously Taleb's criticism of Nate Silver's election forecasting?

Taleb makes the claim in this paper (and others) that there exists some sort of bound on the variance of a binary forecast such that if a forecaster's binary predictions exceed the bounds on variance ...
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1answer
844 views

How can I forecast the Exponential Moving Average of the next day?

I am trying to forecast prices with exponential moving average method. The equation for EMA = [(Closing * k) + (EMA(y) * (1-k)] where: Closing is closing price of today, k is the weighted multiplier, ...
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1answer
300 views

Exponential Smoothing - Alpha greater than 1

Simple stats question. I'm having trouble finding anything in the literature as to why the smoothing coefficient can never be greater than 1. This question was started by me doing time series ARIMA ...
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1answer
63 views

Generate scenarios of multiple related parameters

Assume I have three industry datasets: interest rates, inflation and unemployment. Data contains information of last ten years and it's monthly. Now, I would like to create N possible scenarios of ...
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0answers
64 views

Predicting stock returns using principal components of macroeconomic variables

I'm trying to detect return predictability by regressing stock returns on the first couple of principal components of a set of macroeconomic variables. I'm doing this for different stock styles such ...
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4answers
304 views

Predicting portfolio returns

I suppose there are roughly two approaches to predict portfolio returns. Either predict the returns of all underlying stocks and aggregate all individual stock predictions, or predict the portfolio ...
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0answers
45 views

bond yield forecasting

About the problem of interest rate forecasting I find various paper that address the problem from the perspective of risk premia and affine term structure model. For example Cochrane and Piazzesi (...
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2answers
449 views

What is the best GARCH model for forecasting daily stock return and why?

If I want to forecast daily stock return let say Apple what would be the best GARCH model and why? (ARCH, GARCH-M, IGARCH, EGARCH, TARCH etc)
4
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1answer
65 views

How to prove that the expected squared error associated with the optimal combination weight is smaller than the minimum of 2 forecast variances?

I am looking at linear combination of two forecasts (Bates and Granger, 1969). I would like to understand how to prove that the expected squared error associated with the optimal combination weight is ...
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0answers
69 views

Why can the t-bill rate forecast stock returns?

The tbill rate is used as a predictor of the equity premium in a number of papers. Whilst there is not a general consensus about whether it is a significant predictor, it is still widely used. I ...
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1answer
282 views

GJR-GARCH model using garchFit function

I'm trying to use the garchFit function described here in order to define a GJR-GARCH model to estimate volatility and then forecast VaR. I tried using ...
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4answers
124 views

How to test the linearity assumption of a model?

Let's say I want to have a model that projects income over a stressed period. I have a marked-to-market component that shows the P&L of trading book positions during this stressed period. Along ...
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0answers
2k views

Rolling forecast using GARCH model

EDIT This is not a duplicate of my original question linked, since I have since overcome that problem and have posted an answer. Since solving the previous problem, I have run into the problem ...
2
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1answer
2k views

Is this the correct way to forecast stock price volatility using GARCH

I am attempting to make a forecast of a stock's volatility some time into the future (say 90 days). It seems that GARCH is a traditionally used model for this. I have implemented this below using ...
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0answers
602 views

Poor results forecasting stock price volatility using Python's GARCH model

As far as I understand, forecasting stock price volatility should be more achievable than forecasting absolute prices or returns. It seems as though GARCH models are the traditional and most widely ...