Questions tagged [forecasting]

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1answer
55 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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0answers
30 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
49 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
49 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. ...
2
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1answer
74 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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0answers
41 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
30 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
58 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
89 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
43 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
35 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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0answers
25 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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0answers
27 views

Market implied probability of central bank rate change

Recently, I've come across this article, which is offering a simple model for estimating the probabilities of interest rate cut/hike from the Central bank. This is done by using market data, ...
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2answers
179 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 ...
4
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2answers
176 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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0answers
16 views

How can I calculate forecast returns given volatility and mean forecast?

I have built a model for mean and volatility forecasting of SPY. Now I want to combine these two into a return forecast. For doing this, I have written the following code in R: ...
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1answer
83 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
39 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....
2
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1answer
99 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
24 views

Forecast dates and related actions

My question is quite general and is about the coherence between forecast horizon, then forecast dates, and related actions. As example we can keep in mind the asset allocation problem. It seems me ...
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0answers
82 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
77 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 ...
2
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1answer
273 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
368 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
167 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
56 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
63 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
249 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
44 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
296 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 ...
2
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0answers
68 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
182 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
105 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
1k 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
1k 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
467 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 ...
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2answers
89 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 ...
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3answers
3k 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 ...
2
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1answer
167 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 ...
4
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0answers
107 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 ...
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0answers
56 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 ...
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4answers
461 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 ...
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1answer
113 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
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1answer
325 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 ...
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1answer
40 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
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2answers
200 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 ...
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0answers
79 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
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0answers
242 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 ...
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1answer
107 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, ...