Questions tagged [forecasting]

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15
votes
5answers
1k views
+50

Why quants think that the risk-neutral measure should not be used for financial forecasting?

In posts regarding the $\mathbb{P}$ vs $\mathbb{Q}$ debate (see 1, 2, 3 or 4), most answers conclude that historical-based methods are better suited than risk-neutral models for financial predictions. ...
9
votes
2answers
2k views

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/...
3
votes
1answer
562 views

Forecasting conditional returns in DCC-GARCH-copula approach in R

anyone who could help me interpreting and modifying this code? I have a dataset and want to reserve the last 100 returns for out-of-sample analysis. After specifying and fitting the garch-spd-copula, ...
3
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4answers
155 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 ...
0
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1answer
73 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 ...
0
votes
4answers
146 views

Filling a few missing data in time series?

I'm writing a paper about Uncertainty indices like VIX, etc. I already collected all data but it seems that some of the variables got a few or a little more missing data. I have daily and monthly data ...
0
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1answer
50 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 ...
1
vote
0answers
49 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 ...
2
votes
1answer
147 views

How to interpret and define statistics of GBM output

I am trying to model the future prices of a number of commodities. For this, I am applying geometric Brownian motion, writing a Monte Carlo code in Python. Given that I want to estimate tommorows ...
2
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0answers
37 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 (...
-1
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2answers
116 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)
36
votes
4answers
9k views

What types of neural networks are most appropriate for trading?

What types of neural networks are most appropriate for forecasting returns? Can neural networks be the basis for a high-frequency trading strategy? Types of neural networks include: Radial Basis ...
4
votes
1answer
58 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 ...
3
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0answers
63 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 ...
0
votes
1answer
44 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 ...
0
votes
4answers
94 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 ...
2
votes
1answer
136 views

Why does computing correlation between index levels vs. percentage changes yield completely different results?

I am examining the relationship between the S&P 500 and the Industrial Production Index. Computing the correlation between these these variables yield vastly different results if expressed in ...
0
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0answers
195 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 ...
1
vote
1answer
238 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 ...
31
votes
6answers
7k views

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 ...
0
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2answers
70 views

Financial forecasting and Optimal order submission [closed]

For instance, If i have a model that can accurately forecast 3s ahead, would the trading logic be rather trivial? I have fit a series of distributions to L2 data and believe I have a fairly good grasp ...
1
vote
0answers
132 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 ...
1
vote
2answers
1k views

Predicting stock returns with GARCH in Python

I have seen this post: Correctly applying GARCH in Python which shows how to correctly apply GARCH models in Python using the arch library. Now I am wondering how I ...
3
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0answers
82 views

Comparison of normalization methods on market returns

I am looking to use a multi-factor model to make target-return predictions. Since the factor-returns come from different scales I need to normalize first. There are different ways to normalize ...
1
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0answers
38 views

Forecasting time series data using auxiliary information and associated questions

Suppose I want to forecast MSFT time series, using MSFT history as well as SPY history. Are there good time series forecasting methods that permit auxiliary data to be used? Perhaps you should just ...
25
votes
8answers
12k views

How are cryptography and speech recognition technology applied to forecasting financial markets?

One of the answers to my previous question regarding the strategy of Renaissance Technologies, there was a reference to The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly ...
1
vote
1answer
178 views

Why is the expected value of bias statistic one?

I have been reading about factor models recently. One of the ways in which the developer of these models (Barra/ Axioma) measure the accuracy of their models is by calculating the bias statistic for ...
10
votes
3answers
985 views

Why is volatility said to be persistent?

Persistence in volatility of stock returns is one of the common 'stylized facts' when it comes to analyzing time series. However, I am wondering for theoretical arguments why (estimated) volatility ...
1
vote
1answer
92 views

What is the optimal approach to “backcasting” alternative asset classes (i.e. PE, Hedge Funds, Real Estate)?

I am interested in coming up with better risk calculations for alternative asset classes. As these are illiquid, not a lot of historical data is available. My idea is to use performance of stocks ...
1
vote
1answer
129 views

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 ...
-1
votes
1answer
37 views

How to interpret the accuracy result of the forecaste?

I'm trying to forecast the vacancy rate of multifamily rental property. I have the data from 1992 until today. I'm trying to fit a model with the serie without the last 2 observations. I only need ...
3
votes
1answer
718 views

Please advice free Java library for classical time series forecasting

I've got an ARIMA model (with a GARCH model for variance estimation) and parameters estimated in Matlab for my set of data. Now I need to use this model in my Java based application for making ...
1
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0answers
63 views

Probability of outlier events for laplace distribution

I've read that the laplace distribution is better for forecasting purposes than the normal distribution due to it better accounting for fat tails. However, when I run the numbers in matlab, laplace ...
3
votes
1answer
203 views

Data of Credit Migration Matrices

Please advise that how to get the data of credit migration matrices There is a paper of credit migration matrices, I would import the data to Matlab or R for credit analysis. https://www....
3
votes
0answers
97 views

What is the purpose of short rate models?

Just venturing into quantitative finance and studying short rate models (Vasicek, CIR, Hull-White etc.). Wanted to ask a very simple intuitive question. How would a practitioner use these models? I ...
1
vote
2answers
103 views

Does forecasting asset returns by default assumes non-stationarity of asset returns?

If we assume the assets returns are stationary then the best forecast can only be the mean of the distribution. But if we assume non-stationarity we are forecasting the mean parameter (assuming ...
0
votes
1answer
82 views

Bond asset class long term assumptions [closed]

How are long term capital market expectations set in the industry? I'm looking to get some pointers about setting long term assumptions for fixed income asset classes like global high yield credit, ...
30
votes
5answers
7k views

Any research on how natural language processing can be used to forecast stocks?

Is there any published research of decent quality linking news or unstructured information to asset returns? I know that Thomson Reuters offers its Machine Readable news (MRN), so somebody must use it....
-1
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1answer
251 views

Accuracy for GARCH models

How does one calculate the accuracy of forecasts given by GARCH models considering GARCH is run on returns. Assuming GARCH is a derivative of a regression based prediction model, would regular ...
11
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4answers
2k views

Why are stock index futures not used to forecast how much the stock market will rise, given that interest rates futures are used for this purpose?

In news articles, the reader often read interest rates forecasts calculated based on interest rate futures. An example is here; How did traders calculate that the expected number of rate hikes is 4 ...
1
vote
0answers
47 views

Minimum Lower Partial Moment (n=2) hedging ratio

I would like to better have understanding on the minimum-LPM hedging. I have understood that the co-LPM matrix cannot be modeled by GARCH type models that are used to estimate to the covariance matrix,...
4
votes
0answers
116 views

How to find a probability of VIX moving from one price to another

I asked a similar question on here with a bounty. I decided to modify the question to simplify what I am trying to do. Is there a package on MATLAB or some other tool where I can find the probability ...
5
votes
2answers
253 views

Predicting the Future FX Spot Rates

Say I need to predict what the spot rate between USD and CAD will be in 3 months. What will be the most accurate measure or model that I could possibly use? Does the 3 month forward rate necessarily ...
1
vote
1answer
71 views

$R^{2}$ Measure for Functions (Yield Curves)

I am used to applying $R^{2}$ (relative explained variance) as a measure for point estimates. I am now confronted with forecasting the whole of the yield curve and would like to see what fraction of ...
0
votes
0answers
68 views

Is there a mathematical way of showing the slowing down of economic markets?

I'm currently taking a introductory mathematical finance course in university and recently on the news (BBC, etc), it states that the economic markets are shown to be slowing down for the next few ...
2
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0answers
110 views

What is a good algorithm to predict volatility in metals commodity markets? [closed]

I'm trying to create a script to predict major swings in the price of Aluminium. I am trying to implement a dynamic time warping algorithm for the same. Was wondering if this really is the best ...
1
vote
1answer
435 views

Starting values for constrOptim() in R

I want to perform a constraint optimization for Maximum Likelihood Estimation in R to forecast volatility of returns. The probleme is that my initial values aren't in the permitted region. Is there ...
1
vote
1answer
442 views

How to know if a time series is trending or mean reverting?

I came across Michael Halls-Moore article on using the Hurst exponent test to determine if a price time-series is mean-reverting, trend-following or closer to a random walk, but doesn't this disregard ...
0
votes
2answers
3k views

Can I forecast stock returns using GARCH?

I know this is a rookie question, but I have seen some comments about using GARCH to forecast stock returns. Is it something people do? Wasn't GARCH just for volatility? Also, can you suggest any (...
1
vote
0answers
116 views

Wavelet transform (the à trous time-based decomposition) in R

I urgently need to know how to apply the 'à trous' time-based decomposition in R [also known as Stationary Wavelet Transform] on a time series as a preprocessing, to use the result in forecasting and ...