Questions tagged [time-series]

A temporal sequence of events measured at discrete points in time.

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15 views

Being confused with how the author describe the time frame in a DID setting

Dasgupta,2019,p.2597 said that the treated group comprises all firms that are headquartered in countries that have passed a leniency law by year t. The control group comprises firms in countries that ...
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96 views

Are return time series ergodic?

It seems intuitive to me that return time series would be ergodic. Is there a test statistic that I can use to check this? Would this be affected by sampling rate? One way I can think of checking ...
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Statistical methodology for proving the stability in time of asset allocation weights

I am comparing the set of weights obtained by the classical Markowitz allocation process with those of another asset allocation technique I have devised. Markowitz's weights are unstable, as the ...
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23 views

FamaFrench, FamaMacBeth or Panel regression?

I hope my question is not extremely trivial. I want to analyse the performance of mutual funds using the Fama-French model. My dependent variable is the return of mutual funds (varying over time and ...
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45 views

Show that $\text{Cov}[X_r,X_s]=\text{Cov}[X_{r+h},X_{s+h}]$ for $X_t=a+bZ_t+cZ_{t-2}.$

Problem: Let $\{Zt\}$ be a sequence of independent normal random variables, each with mean $0$ and variance $\sigma^2$, and let $a$, $b$, and $c$ be constants. Is $X_t=a+bZ_t+cZ_{t-2}$ a (weakly) ...
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66 views

Bad plots in python, good plots in excel

I am wondering if you could solve the mystery about why matplotlib / seaborn give me a line plot of the IBM stock price, which is terrible as you can see below, with some vertical lines that are of ...
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137 views

Show that $Y_t$ and $Y_{t+h}$ are independent if $X_t$ is Gaussian

If $Y_t=\sum_{i=0}^qa_iX_{t-i}$ where $X_{t-i}$ is Gaussian with mean $\mu$ and variance $\sigma^2$, how do I show that $Y_t$ and $Y_{t+h}$ are independent (for $|h|>q$) using the joint pdf. I know ...
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142 views

Question about slides in lecture note: What if we can't assume $\mu=0?$

The question popped up when I was reading these lecture notes online. Consider the MA$(1)$ process given by $X_t=W_t+bW_{t-1}$ where $W_t$ is white noise distributed with constant variance $\sigma_W^2....
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46 views

Estimating distribution of rate of return

Let $f[t]$ be the price of a stock at time $t$. We can calculate the rolling rate of return of the stock in a window of length $n$ by computing: $$r[t] = \frac{f[t] - f[t-n]}{f[t-n]}$$ $r[t]$ is ...
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42 views

CAPM: Testing for alphas jointly equal to zero

For my project, I need to assess if a certain factor X leads to a CAPM-Anomaly. First, I sorted the monthly stock return (sample size: 500+ observations) according to the X factor in 10 decile ...
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81 views

Show that $\text{Cov}[Z_t,Z_{t+h}]=\text{Cov}[Z_s,Z_{s+h}].$

Problem: If $X\sim\text{WN}(\mu,\sigma^2).$ Let then $Z$ be the process defined by \begin{equation} Z_t=\sum_{i=0}^na_iX_{t-i} \end{equation} for some coefficients $a_1,...,a_n\in\mathbb{R}$ with ...
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54 views

Is the mean of a stationary timeseries the same everywhere?

Say for example I have the white noise process $Y_t\sim\text{WN}(\mu,\sigma^2)$. Is it true that $\mathbb{E}[Y_t]=\mathbb{E}[Y_{t-h}]$, where $h\in\mathbb{N}?$
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How to compare or prove economic/statistical similarities between two models with differing independent and dependent variables?

I have two datasets: The relationship between Bitcoin prices and other cryptocurrencies. The relationship between EUR prices and other currencies. What would be the most appropriate way to prove ...
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34 views

Calculation of Expected Shortfall using IMA Approach ( FRTB)

I am trying to calculate the Expected shortfall of a FX portfolio through IMA Approach of FRTB in excel . I have used several combinations in excel to get the liquidity horizons and then calculate the ...
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30 views

Hedonic regression to create an index?

I’m having a hard time understanding how hedonic regression can be used to create an index. Hedonic regression seems to simply be multiple regression by a different name, correct? We have several ...
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46 views

What is the best approach to modeling local time series house prices?

I have a dataset of house prices over time and have broken it down into neighbourhoods. For each neighbourhood I would like to create a time series model that captures the local price movements. What ...
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133 views

Backshifting Price Timeseries with Memory Preservation

In Advances in Financial Machine Learning the author makes a case for fractionally differentiated price returns in chapter 5. The reason is to both maintain memory and to generate a stationary time ...
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63 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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39 views

Variance ratio test and ADF test for random walk

I am trying to use both ADF test and variance ratio test for random walk. However, the ADF test tells me my financial time series contains unit root, but variance ratio test (lo-mackinlay) rejected ...
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Do I use % return, log return or diff of prices to plot ACF?

I am reading a book on time series. To make a non-stationary series stationary, sometimes we need to difference the series. When it comes to finance, prices are non-stationary. Many authors fit ARMA ...
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93 views

How are the values of the ARMA process linked in python

In the code below, you can see that 'ret' is an ARMA process, and I am trying to see how the ret[0], etc... ret3, ret4, etc. are linked to each other, and although I know the formula for the ARMA ...
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40 views

weekly returns and the daily returns scaled to weekly

I am new in this blog and first of all I want to apologise for my english. I have to calculate, for a university project, the weekly returns and daily scaled returns to weekly for few stocks For ...
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35 views

Calculating the downside correlation between two time series

If I have two financial time series and I want to calculate the correlation between them when series1 gives me a negative returns, would that be as simple as picking only those periods where series1 ...
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22 views

Year on Year growth percentages vs share price returns

Say I have 2 time series A and B. A is a time series of year-on-year growth numbers at quarterly intervals (I don't have the index levels). For example a data point as at 30-Sep-20 of +17.7% ...
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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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79 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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59 views

Forecasting returns and volatility using ARIMA-GARCH model in R

I am using rugarch package in R to forecast returns and volatility of a stock. I train an ARIMA (p ,d q) + GARCH(s, r) model on ...
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35 views

What does p-value adjustment under FWER do?

The background is I am predicting a time series with three strategies, the hypotheses is the strategies have a non-zero Sharpe ratio. I am reading Backtesting, by Campbell Harvey and Yan Liu paper in ...
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57 views

Electricity Futures Risk Premiums With ARIMA

I am attempting to model long-term electricity prices using today's futures prices. Unlike most futures, electricity is delivered over a period of time (usually a month), rather than at a point in ...
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35 views

High Frequency financial data [duplicate]

I really need high frequency data for my thesis. The data should contain the following columns: Time with format: yyyy-mm-dd h:mm:ss; Price; Bid price; Ask price; Bid volume; Aks volume; volume I ...
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26 views

How to merge two sets of timeseries together while maintaining the same returns?

I have a question about merging two sets of timeseries without causing much havoc. I have to merge dataset 1 into dataset 2. Problem is: The levels are different. (Ex: dataset 1 is moving between 2 - ...
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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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54 views

Modelling Skew when using ARMA Time Series

I am currently modelling financial time series via ARMA processes, but I have reason to believe that in addition to significant autocorrelation, the time series also exhibit skewness. Is there a way ...
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32 views

Examining individual portfolio allocation changes over time

I am currently working with a pretty large panel dataset containing the investment holdings of many individuals over time (i.e., for each individual I know the positions per stock over time). I was ...
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55 views

Should a stock with high return autocorrelation be weighted more heavily in a portfolio?

Some say the presence of autocorrelation (aka serial correlation) in a stock's financial return time series helps with forecasting its next-day movements, unlike a stock that has low serial ...
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34 views

Generate random timeseries in Python

I'm trying to test a particular trading strategy under different assumptions and would like to do so on different random time series. I would like to be able to specify the following: Start price End ...
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39 views

Is it possible to use volume/dollar bars instead of time bars when analyzing multiple variables?

I recently read Marcos Lopez de Prado's book "Advances in Financial Machine Learning" where I was introduced to the concept of using volume/dollar bars instead of time bars. As far as I ...
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146 views

Storing options EOD time series in Flat Files

I have purchased data for EOD settlements of options prices for USA futures for personal use. I will not need multiple user access or real time access. I am not an expert programmer but use C# and R ...
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Computing statistics from historical returns

I'm reading age 35 of "Advances in Machine Learning" by de Prado. Consider an IID multivariate Gaussian process characterized by a vector of means μ, of size Nx1, and a covariance matrix V, ...
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84 views

Cannot achieve generalization of machine learning model

I'm working on a balanced, binary classification problem in a time-series (financial) dataset. I am using K-fold cross validation that is adapted for time-series (so that I'm never using future data ...
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88 views

Best method to determine future success or to determine best linearity?

Long time viewer, but first time poster, so excuse me if i'm in the wrong place please. Anyway, I am working on a project that is pretty interesting. Through data mining, I am able to gather a ton of ...
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57 views

Estimating the variance of returns with aggregated data

Say I have an asset return time series: Jan2020: -5% Feb2020: +5% Mar2020: -5% Apr2020: +5% May2020: -5% Jun2020: +5% Q3 2020: +20% Oct2020: +5 Nov2020: -5 Dec2020: +5 Note that 3 months of data is an ...
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80 views

Style analysis and Kalman Filter

I am trying to implement a code that uses Kalman filter to improve the performance of traditional style analysis. I have come across a paper called "Return based style analysis with time varying ...
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35 views

Defining the Average Length of Business Cycle using AR(p) model

I'm currently reading through Analysis of Financial Time Series by Ruey Tsay. The AR model is introduced in chapter 2 and its properties in 2.4.1. The difference equations are explained and then its ...
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60 views

Predictive power of lagged features [closed]

I have to build a classification model to predict recessions. I have selected a set of features (some are economic and some are financial). I have noticed that it is good pratice often to add to the ...
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Interest Expense Optimization

So I have a problem I need to solve and no idea how to approach it. Its a verbal problem without any specific numbers given except for those below. So it is up to me to determine how to structure the ...
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73 views

Simulating correlated Geometric Brownian Motion with lag

I know that it is possible to simulate two correlated GBM in e.g. Matlab (Generating Correlated Asset Paths in MATLAB) based on cholesky decomposition. However, they take as input the correlation ...
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50 views

Do you need multi-period ahead covariance forecast, in order to construct portfolios with weekly/monthly rebalancing?

Suppose I want to rebalance my portfolio each week. Do I then need weekly covariance forecasts, from some multivariate volatility model to do this? Ie. Insert the weekly covariance forecast $\Sigma_{t+...
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39 views

Squared Residuals equal Variance of Dependent Variable (ARMA-GARCH)

My understanding of ARMA-GARCH models for a variable $X$ is as follows: I estimate a conditional mean of a variable $X$ by use of the ARMA part of the model. I estimate the conditional variance of ...
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30 views

Correlation of financial returns: how to account for different frequencies?

If you had to calculate a correlation between two financial return time-series, on what frequency would it make sense to do so? Yearly returns? Monthly? Weekly? Daily? What is the norm here? The issue ...

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