Questions tagged [time-series]

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

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1 answer
744 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 ...
21 votes
7 answers
3k views

How random are financial data series?

Pseudorandom number generators are often tested using e.g. a test suite like Diehard tests or Dieharder. If one would run these tests e.g. on stock market time series or other financial data, would ...
0 votes
1 answer
78 views

How to implement rolling granger causality

I am investigating two time series where the first is the daily closing stock price changes and the other is the daily changes in the PCE index. I want to investigate how much the PCE index explains ...
1 vote
2 answers
613 views

Trouble Calibrating a Vasicek Model

I have simulated some data according to a Vasicek process and I am then trying to apply ordinary least squares (OLS) regression analysis to see how accurate the estimated model parameters are from the ...
0 votes
1 answer
57 views

Regression taking in account size of earnings surprises

I'm trying to regress earnings surprises on variable x. However, absolute earnings surprises are mostly influenced by company total earnings and the number of shares outstanding. So I can't just use ...
0 votes
0 answers
47 views

Reasons for negative autocorrelation of forward prices

I am working on each trade day's forward prices of gasoline. I noticed that the autocorrelation at lag 6 is significantly negative. I know how to interpret negative autocorrelation in a statistical ...
20 votes
5 answers
2k views

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 forecast are better suited than risk-neutral models for financial predictions....
0 votes
0 answers
104 views

Forecasting VIX with GARCH(1,1)

Aim: Forecast VIX using GARCH(1,1) Reason: I want to be able to forecast VIX on several horizons, in order to be able to forecast the SP500 index through linear regression. Tools used: Python, ...
0 votes
2 answers
159 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 ...
4 votes
2 answers
462 views

Are there alternatives to the Box-Tiao decomposition in identifying mean reverting portfolios?

As documented in this paper, (Identifying Small Mean Reverting Portfolios, by Alexandre d’Aspremont, February 26, 2008) Box-Tiao decomposition (a way to decompose multiple time series into components ...
3 votes
1 answer
670 views

Realized Variance (realized volatility)

I'm confused about realized variance. I roughly know the theory around Ito Calculus and quadratic variation and integrated volatility so I understand what realized variance measures (even though as ...
1 vote
0 answers
75 views

Application of Gramian Angular Field to financial series?

I found this method to represent time series to improve performance of some ML models, any thoughts about this method? some applications or use cases in financial markets?
3 votes
1 answer
254 views

Daily realized volatility and true daily volatility

Can someone help if I am thinking correctly? If $R(t,i)$ is the i'th log-return for $i = 1\ldots,M$ of day $t$ for $t = 1\ldots,T$. Can I assume that the daily realized volatility (denoted $RV(t)$) is ...
1 vote
0 answers
73 views

Techniques for proxying time series / stock prices

What are some good techniques for proxying time series? My purpose is for risk management / modelling and I would like proxy to missing series. Given that I also have to account for volatility, ...
1 vote
1 answer
230 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 ...
0 votes
0 answers
78 views

Inconsistency between simulation and the probability of a "stock" hitting take profit before stop loss

Let's assume a stock at time $t$ is worth $X(t)$. If the returns of $X(t)$ are i.i.d. and normally distributed,the probability of $X(t)$ hitting a value $H>X(t)$ before $L<X(t)$ is $\frac{H-X(t)}...
2 votes
1 answer
282 views

How to determine which realized volatility estimator should be used?

There are so many realized measure have been invented in the past years like TSRV, MSRV, KRVTH, KRVC... But how to choose them in practice? I know we cannot find the "estimation error" of ...
12 votes
1 answer
3k views

Feller Condition (Cox-Ingersoll-Ross) source

For the Cox-Ingersoll-Ross model $$\text{d}r_t = a(b-r_t)\text{d}t+\sigma\sqrt{r_t}\text{d}W_t$$ the condition (referred to as "Feller condition") $$2ab\geq\sigma^2$$ ensures that the solution is ...
0 votes
1 answer
82 views

What are common ways to realistically simulate the stock market using historical market data?

I am currently using the FinRL library to try to automate Trading using Reinforcement Learning. However, I wanted to understand how FinRL simulates the stock market using historical data. I read here ...
17 votes
4 answers
15k views

Why do we usually model returns and not prices?

I think this is a quite similar question for most of you, however it is not completely understandable for me at the moment: Why do we usually use returns and not prices to model financial data in ...
0 votes
3 answers
95 views

database for economic & finance timeseries

I am looking for a technical solution to store economic and financial timeseries (nothing intraday for now, just daily/weekly/yearly) Most timeseries database I find do not seem to take into account ...
0 votes
1 answer
178 views

Memory effect of log returns of S&P 500

I am trying to reproduce the analysis discussed in https://arxiv.org/pdf/cond-mat/9905305.pdf where they use high-frequency data (1-minute frequency) of S&P500 from 1984 to 1996. In particular, ...
0 votes
0 answers
77 views

I.I.D log returns. What about their square?

If one assumes the underlying return process is I.I.D, is there a solution to the question of the autocorrelation of squared returns? Thanks.
3 votes
1 answer
335 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 ...
0 votes
1 answer
83 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 ...
8 votes
2 answers
904 views

Is there any research on applying state-space or dynamic linear models to forecasting equity risk premia?

Is there any research on applying state-space or dynamic linear models to forecasting equity risk premia on a security-by-security basis with a medium term horizon (say 3 month to 12 months horizon)? ...
1 vote
4 answers
140 views

Looking for options to visualize large market timeseries data

I have a large dataset that includes my strategy back-test run data. The dataset columns include candle date, close price and many strategy related data. I’ve built a Mathplotlib visualization for my ...
0 votes
2 answers
183 views

comparing volatility and correlation over time

I'm trying to figure out if some emerging markets change over time. First of all I am going to check for changes in volatility. What would be a good method to do this. And do you suggest comparing ...
1 vote
2 answers
248 views

2-day ahead prediction of value at risk with GARCH(1,1) in R

Let's say I have a 10 year dataset of Tesla (example) and I am taking the percentage change of lag 2: ...
0 votes
0 answers
74 views

Filling in between data in finance

I'm trying to create a model on how different factors influence a particular asset. For some of these factors, like inflation, for example, I have monthly data, while for others, like exchange rates, ...
2 votes
0 answers
134 views

Copula Models for Asset Returns

I'm learning about copulas and their applications in finance. When used to assess the dependence structure between two indices for example, can the copula models be estimated directly on the log-...
0 votes
2 answers
328 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 ...
3 votes
1 answer
196 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 ...
0 votes
0 answers
68 views

How to find out the dates of the different financial quarters (e.g. Q1, Q2, etc.)?

Question: Is there any resource I can use to find a list of dates which constitute the start and end of the 'financial' quarters (e.g. Q1, ..., Q4) for the years 2006 onwards? I know sometimes they ...
0 votes
0 answers
46 views

How to compute the combined probability of loss for 2 time series (consisting of historical stock prices)?

May I please ask the community's support with the following problem? I have 2 time series, with approximately 1000 observations each (same number of observations for both). They represent the daily ...
0 votes
0 answers
67 views

PCA on portfolio depending on multiple time series

There is extensive documentation about PCA on specific time series (for example the UK yield curve). When you have a portfolio which only depends on the change of the UK yield curve then a PCA on the ...
1 vote
1 answer
175 views

Simulating the Value-at-Risk with $t$ distributed returns

I want to understand how the value at risk and the simulating the VaR with simple Monte Carlo method. But I want just a confirmation and are welcome any comments, since I don't have the full picture ...
0 votes
1 answer
173 views

Conditional Value at Risk using GARCH models

In this paper: https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwjSlIHYnMj1AhWqNOwKHZfHDhkQFnoECAkQAQ&url=https%3A%2F%2Fwww.mdpi.com%2F2076-3387%2F9%...
0 votes
0 answers
161 views

Data science techniques for intraday trading

I am a Masters student in data science looking to get into a financial-themed project related to intraday trading. This will not be HFT, so the frequency will be somewhere around 1 or 5 minutes. I am ...
1 vote
0 answers
87 views

What does M^L represent over this Sigma?

This is throwing me for a loop. in regards to this passage, does the M^L represent to perform this sum over every "overlapping window" individually? Would this mean "M symbols" are ...
0 votes
4 answers
381 views

Imputation of missing returns

I'm trying to calculate a historical VaR for a portfolio of futures, however there are certain days for which some assets are missing prices. Since the portfolio consists of many spread positions, the ...
0 votes
0 answers
22 views

How to derive Level 2 Market data from Order book of energy trading market over custom intervals

I am looking for resources which provides details like which model/logic/algorithms being used by Energy Exchange and other OTC market to sequence and display best 5 or 6 bid and offer prices (Level ...
0 votes
0 answers
91 views

Time series data for probability of default (or credit ratings)

I'm currently investigating potential correlations among ESG ratings and credit ratings; more in particular, i'm trying to understand whether such correlation evolved during the last 20 (?) years, and ...
1 vote
1 answer
237 views

How to deal with negative intercept terms on GJR-GARCH(1,1) model?

Recently, I have been studying the relationship between COVID-19 and stock returns using a GJR form of threshold ARCH model. However, I got some unusual estimation results I can't figure out whether ...
1 vote
0 answers
94 views

Why is the moving average called that way? [closed]

I am a beginner in time-series analysis. The moving average model uses past errors*parameter, so why is it called a moving average model? It seems counter-intuitive to me. The Auto-Regressive model ...
1 vote
1 answer
213 views

Does it make any sense to normalize returns?

I have been going through a course for Time Series Analysis. First we learned to make returns from a time-series of stock index by (Xt - Xt-1)/Xt-1 . This makes the series stationary, which means we ...
1 vote
1 answer
122 views

Persistence and stationarity together in volatility analysis

I am trying to analyse a time series. I want to get only quantitative results (so, I'm excluding things like "looking at this plot we can note..." or "as you can see in the chart ...&...
0 votes
0 answers
77 views

Machine learning models for sequential truncated time series ahead of a series of events

After some unsuccessful searches, I am turning to the community for the following issue: Assume I am interested in the dynamics of a stock prior to FOMC meetings. I am interested in the 20 days prior ...
0 votes
0 answers
126 views

Calculate and study volatility time series

I am trying to study a time series. I have 10-year daily close prices for some stocks, so my time series is very simple: each day I have a close price for my company. The question is: how can I want ...
2 votes
1 answer
367 views

Understand the white noise condition in Vector Autoregression

In the following vector autoregression model with lag polynomial representation: $$\Phi (L) y_t= \epsilon_t$$ where $Y$ is the vector of endogenous variables, $\Phi$ is the parameters matrix, $\...

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