Questions tagged [time-series]

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

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26 views

In your experience, when trying to predict something that occurs, do you model with a fixed time period?

Let's say you are building a simple model (like the classroom examples) of trying to predict, given past information, if the stock goes up or down in the future. One could, like in classroom examples, ...
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23 views

How to Compute the Return for a Series of Investments with Payouts?

I am looking for a metric to track the performance of investments in a security over time. I know what I have in mind but I am not sure how to map it onto a known metric. I want to answer the ...
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35 views

Cumulative returns are more correlated than non-cumulative

I was just comparing two daily returns series and noted that the correlation between them is a lot higher if they are cumulated (about .95 for cumulative returns, vs .15 for non-cumulative). I feel ...
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33 views

Conditional and unconditional variance, autocovariance and autocorrelation of an ARMA process

Given an ARMA(1,1) process $x_t = a + bx_{t-1} + \varepsilon_t + \theta\varepsilon_{t-1}$, how can we find the conditional variance, i.e. $Var_{t-1}(x_t)$, find the unconditional variance, i.e. $Var(...
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70 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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11 views

Do volume/dollar bar series always have less observations than time (bar) series?

Traditionally, financial returns are derived from prices that have been sampled based on constant time intervals. These are known as time bars, and a series of returns based on time bars are what we ...
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12 views

How to simulate the cross-section

I am looking to simulate the whole cross-section of daily return series for 20 to 60 days. The purpose is to test some risk measures based no maximum drawdown. Thus, it needs the whole time series. ...
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31 views

Using unsupervised classification to find support and resistance levels

I do not have a specific question, it's more of a general & conceptual one. What would be the optimal approach to finding support and resistance levels? Have you approached this problem ...
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20 views

Why would this price data have lots of spikes above the trend line?

I am completely new to quant finance, so I apologise if this is a ridiculous question. Here is a picture of a snippet of some price data from the security 'NYSEARCA: SPY' (which is SPDR S&P 500 ...
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1answer
40 views

Serial correlation, quadratic variation and variance of returns

On p. 3 of Lorenzo Bergomi's book on Stochastic Volatility Modeling, there is the following assertion: Indeed, to a good approximation, the variance of returns scales linearly with their time scale, ...
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48 views

Options pricing model inversion

He cited about Roll's compound formula for finding the lead-lag effects between stocks and options. I have a similar data for National Stock Exchange's Index, NIFTY but it's daily, not intra-day. I ...
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78 views

lead lag relationship among futures, options and stock prices

I have the data of past 10 years of NIFTY (the National Stock Exchange of India) stock, futures and options and I want to show the lead-lag relationship (which reacts first, futures, options or stocks)...
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14 views

Statistical test for comparing two different speed of mean reversion parameters for CIR model

I am trying to compare two different values of speed of mean reversion parameter for CIR model. I would like to know if there exists a statistical test for comparing these two parameters. the estimate ...
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24 views

CIR-Model with regime switching Mean-Reversion level - Hamilton Algorithm

I am trying to implement the Algorithm from (1) in R, using the same approach as in (2) and respectively. The main idea is that $x_t$ follows a CIR-process and that the parameters of the latent ...
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1answer
44 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
92 views

Turning a covariance sum into an integral

I am reading Lorenzo's Bergomi's book Stochastic Volatility Modeling, and I have come to this passage. I just would like to understand the derivation between the first and the second equality. I ...
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87 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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20 views

PanelOLS or simple OLS?

It is probably a silly question but please assume the following. I gather hedge funds returns and I want to do a regression against few dependent variables (FF factors, etc.). In essence, I get a ...
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1answer
46 views

Volume bars, dollar bars from low-frequency data?

Financial models by default use time bars of prices/returns for input data. I use time bars to refer to both intraday (high frequency) and interday (low frequency) data since the sampling occurs at ...
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1answer
47 views

Portfolio optimization with multivariate returns of different length

The mean variance model of Markowitz that uses multivariate covariance matrix requires the length of each of the N assets return time series under consideration to be of equal length. Are there any ...
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22 views

How to set up the dummy variable for OLS event study regression

I've been going back and forth with how I should work to find an event effect. would be so grateful for some clarification. I have daily time series of exchange rates for different countries ( 1 for ...
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1answer
44 views

Sampling and cross-validating with tick, volume and dollar bars

Financial data is usually structured with time bars. Other sampling techniques include: tick bars volume bars dollar bars. These are so-called sampling techniques to better identify signals and ...
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2answers
87 views

Converting time bars to tick bars or volume bars in python

Recently I've started reading Advances in Financial Machine Learning by Marcos Lopez de Prado. In the second chapter the author defines some essential financial data structures, like tick bars, volume ...
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What is the correct order of operations when cleaning and structuring financial time series?

I'm studying Lopez' Advances in Financial Machine Learning where he talks about how to sample and structure financial data, as well as how to apply machine learning models to the data. I am also ...
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25 views

How to get daily S&P500 dividend and CPI data?

For a project where I'm modelling asset prices using heterogeneous dividend expectatations, I want to investigate the effect of the COVID-19 virus. This means I'm looking at daily stock price data ...
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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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11 views

Engle-Granger Regression for returns or prices?

Im trying to find a cointegration relationship between a spot and futures series as I'd like to compute the optimal hedge ratios. As I find the spot and futures at the price level to be nonstationary, ...
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1answer
57 views

Align volume bars for multivariate analysis

Looking at the book "Advances in financial machine learning" the author proposes a way to sample high frequency financial data in several fashions which are not only the standard time bars. I was ...
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2answers
193 views

Is there a way to tell if a time series price data is reversed?

Assuming you are given an array of values representing a stock's historical price, without timestamps, is there a way to tell if this array of prices has been reversed?
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1answer
61 views

Backtesting with a walkforward approach

I am setting up a backtesting using a walkforward optimization model to find out if a trading strategy performs well or not and I would like to clarify some doubts: First of all what is the correct ...
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1answer
35 views

What value to put in lm() function when testing for cointegration (R)

I'm a CS student working on a financial computing project + have a question regarding cointegration testing using linear regression with the lm() function. https://www.rdocumentation.org/packages/...
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31 views

Performance attribution and monthly rebalance: Is a month enough data to calculate Beta and Alpha?

A portfolio is built systematically by calculating scores and rebalanced each month to invest only in the 80 best scores. Scores change frequently and therefore the portfolio changes each month, ...
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1answer
23 views

Performance attribution of indices to their sector weights

Is it possible to attribute performance of indices (monthly returns and risk measures - Sharpe ratio, etc.) to their sector weights (if I know them)? Example: I know the monthly performance of ...
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19 views

How to set constraints on the VAR matrix of a Markov-switching VAR model in R?

I’m trying to estimate a Markov-switching VAR model in R and I want the autoregressive matrixes to be constant across the states. In other words, only the intercepts and the covariance matrixes are ...
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10 views

What is a clear and broad statement about stationarity requirements on features, and then on target for some type of learning to be possible?

I see a lot of vague statements about time series analysis and stationarity but they are all very unclear. I am looking for clear statements on a) the features b) the target c) the learnability of ...
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1answer
56 views

Decay factor and volatility (2 assets): do you keep simple correlation to calculate vol? or exponentially weighted correlation?

I have calculated exponentially weighted variances (and covariance) for a future and the underlying index. Now that I have exponentially weighted variances for my 2 assets using a lookback period of ...
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1answer
53 views

Can ARMA and GARCH models be estimated separately in ARMA/GARCH?

Can I use the residuals of the ARMA model to build a GARCH model(with Zero mean)? If so, does this mean that this GARCH model(with Zero mean) has no effect on ARMA's estimates. For example, if I want ...
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1answer
81 views

How to apply decay factor in the volatility calculation for 1 asset?

I read somewhere that the decay factor is (1-lamba)*lamba^t where t is first return, second return, third return, ... I also found this formula which I have difficulty to understand: How do I ...
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1answer
69 views

Use futures contracts of different lengths to predict spot prices

So I am trying to see how future contracts prices with different time to maturity are able to predict the actual spot price of crude oil at the time of maturity for the contracts. I have the simple ...
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1answer
48 views

How to use multi-periods and mult-factors to predict stock price by linear regression?

Give data in $t_n$ denoted by $[x_1^n, x_2^n, ... x_d^n]$ and label $y_n$ to be predicted. We can just train a $d$-dimensional linear regression $y_n=\sum b_ix_i^n$ to make a prediction. However, I ...
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1answer
59 views

Predicting time series based on another

This is more of a generic question, but I'm sure it has a best answer/methodology which is what I'm trying to reach. I'm trying to figure out a solid line of thought when looking at a time series X ...
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1answer
96 views

R: Finding peaks on a stock price chart

I would like to do is what I thought to be a simple task: find the locations of peaks for a certain stock, and mark those peaks on a chart. I was surprised by a lack of appropriate examples on the ...
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1answer
112 views

GARCH(1,1)-M MLE optimization with fmincon in R

I've searched thru dozens of papers and did not find in any of them satisfying and enough theoretical answers to my concerns. So I've combined everything what I found below. Please indicate if my ...
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32 views

R-Help..Question regarding working day Frequency in Time series

I have a data where there are observations based on working days in a year. The working days are not same in each year. These are 248 (say in 2018) observations in first year and then may be 246 ...
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1answer
34 views

Relationship between Data Size and Arima Prediction Interval Width?

When we use Arima model to acquire Interval Predictions, will the width of prediction intervals decrease if we use more data (longer history) to fit the model?
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2answers
45 views

Updated Time Series Prediction Model When acquiring new data Points - Basic Question

Suppose I have a Time Series Model (assume ARIMA) and use it to make one-step ahead prediction. If I acquire a new data point, (for example I was originally using the first 100 days to fit an Arima ...
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136 views

Process Transforms (Fractional Difference)

Let's say I have a process $X_t$ with unknown variance process $V_t$. Then, I write $\mathrm{EMA}[X_t]$ to be the 5 sec exponential moving average of $X_t$. Consider the transformation $$\sum (X_t-\...
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56 views

How to compute prediction interval if using simple moving average t o predict?

If I want to use simple moving average to make a prediction. For example given h=1 and m=13. $\hat{x}_{t+1}=\frac{\sum_{j=1}^{13}x_{t-j+1}}{13}$. What is the prediction interval going to be? How to ...
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17 views

Log Transforming My TS Data for a First Difference Regression

I'm currently working with a ts of monthly yields where $Yield = \frac{Expense}{Blance}$. I am trying to understand the change in yield given a change in the market rate. My regression is $Y = \...
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33 views

Calculating the total return on an Interest Rate Swap (with 1 year of duration)

Say I am the fixed rate payer on an interest rate swap and have 1 year of duration of exposure. When I entered into the IRS (say yesterday), the quoted rate on Bloomberg was 15%. Say tomorrow the ...

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