Questions tagged [forecasting]

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126 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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125 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 ...
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242 views

Rolling window Kendall's tau against APARCH(1,1) correlation

Assume you want to forecast the correlation matrix of a stocks' basket (say 15 ~ 20 stocks from different sectors); assume you need to forecast at $T$ days because you will use the forecast ouput with ...
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1answer
2k views

Moving window forecasting in Python

I am looking to create some code that will out-of-sample forecast the HAR-RV model. The model itself is formulated as the following, and the betas are estimated through HAC-OLS or Newey-West. ...
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3k views

QLIKE loss function to evaluate forecasting model of log(realized volatility)

I use QLIKE as loss function to evaluate the forecasting performance of a RV realized volatility model. QLIKE = log $h$ + $\frac{\hat{\sigma}^2}{h}$ where $h$ is volatility forecast and $\hat{\sigma}...
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700 views

GARCH modelling and forecasting

I have a few questions regarding GARCH modelling and forecasting and it would be great if someone could help me. I am modelling the log return of oil spot prices using various GARCH models: GARCH, ...
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555 views

Oscillatory time-series forecasting

I was wondering if this mean(160)-reverting/oscillatory time series "SUM" can be considered chaotic & forecastable to some extend short-term? http://sg.myfreepost.com/sgTOTO_analysispower.php?...
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64 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 ...
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89 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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47 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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72 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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173 views

Risk neutral probability and forecasting

When our goal is pricing of derivative products we, due to no arbitrage conditions, have to use the risk neutral probability. In other side if we have risk management purpose we have to use the “...
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1k views

Forecast of ARMA-GARCH model in R

I managed to forecast a GARCH model yesterday and run a Monte Carlo simulation on R. Nevertheless, I can't do the same with an ARMA-GARCH. I tested 4 different method but without achieving an ARMA-...
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41 views

Non-overlapping ranges of HCNN' observables and of state transition function

In the artcicle Forecasting and Trading the High-Low Range of Stocks and ETFs with Neural Networks HCNN is used for forecasting of nine time-series, namely: returns of the lows returns of the highs ...
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466 views

Stationarity tests in the frequency domain for regression

Strict stationarity is the strongest form of stationarity. It means that the joint statistical distribution of any collection of the time series variates never depends on time. So, the mean, variance ...
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256 views

Modeling asset performance to Bitcoin revenue

I'm attempting to model asset performance to Bitcoin revenue, which is a driving force in the Bitcoin community. Question Is there any model, or research being done that tracks "hashes per second" (...
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37 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. ...
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0answers
32 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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43 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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42 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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78 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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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
98 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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70 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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640 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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78 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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86 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 ...
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0answers
61 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,...
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152 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 ...
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0answers
134 views

What are the current gold standards for volatility prediction error?

I'm working on volatility forecasting models for equities and currencies. I am using daily data and am interested in producing forecasts for the next n days. To ...
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49 views

How to reduce data dependence for empirically assessing option pricing model performance?

I am preparing a paper about mitigating assessment failures for option pricing models. For the sake of simpliciy, suppose we are talkin about European options. In basic terms, what I would like to say ...
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142 views

ARIMA prediction for currencies

I was browsing TradingEconomics.com and I came across their forecast models which immediately captivated my interest. They describe them as "projected using an autoregressive integrated moving average ...
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0answers
260 views

Relationship between in-sample and out-sample periods length

I have two general questions regarding "in-sample fitting vs. out-of-sample backtesting" kind of analyses. Is there any relationship between the length of the data collected for in-sample fitting ($a$)...
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31 views

What are appropriate algorithms for forecasting contract schedules to maximize profit?

Imagine a situation where a business negotiates contracts for the maintenance of widgets it sells. Situation Customer buys 20 widgets. Customer negotiates contract for widgets to be serviced/...
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47 views

Relative merits of Adjusted versus Closing prices for market predictions

Basic question I am familiar with the data returned from Yahoo. For indices and the like (e.g. ETFs) there are seven columns of data: Date, Open, High, Low, Close, Volume, Adjusted. We only need ...
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339 views

Asset allocation and GARCH models

I am trying to solve an asset allocation problem and I am having some troubles grasping the concept. I am working with excess returns on 4 stock indices and I am obtaining the excess returns forecasts ...
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21 views

Reconciling forecasted growth of components and sum

I'm working with a very basic basic forecast model using Compound Annual Growth Rate and I need to reconcile the forecasts at different levels of detail. Suppose I have two business lines with ...
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0answers
80 views

Cross-sectional moments

I got a seminar topic named Forecasting risk from cross sectional moments? Could at least someone tell me what should I write about and if there is any paper that I could read. Thank you very much in ...
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25 views

In-sample forecast accuracy of Beta (Kalman filter) CAPM

One can calculate time-varying betas (known from the CAPM) using the Kalman filter. For example, one can calculate the in-sample forecast accuracy using the MAE. $MAE = \frac{1}{T}\sum_{t=1}^T|\hat{R}...
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70 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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0answers
26 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 ...
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84 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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0answers
37 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 ...
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33 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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76 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
529 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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29 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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286 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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3k 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 ...
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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 ...