Episode #125 of the Stack Overflow podcast is here. We talk Tilde Club and mechanical keyboards. Listen now

Questions tagged [time-series]

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

Filter by
Sorted by
Tagged with
1
vote
1answer
65 views

Misunderstanding of time series autocovariance

I'm reading the "Time Series: Theory and Methods (2nd ed.)" by P.J.Brockwell and R.A.Davis. I've stopped at the one moment at pp.218-219 (Chapter 7 "Estimation of the mean and the Autocovariance ...
0
votes
2answers
45 views

Significance Of Missing Data for RMSE Estimation

I have a time series covering ten years of daily close prices, which I compare to a theoretical time series generated by a model. The original series has a handful of missing data points (~2%), some ...
1
vote
0answers
64 views

Fama-French 3, Carhart 4, Fama-French 5 Factor models return borderline 0% R2 (max. 6.6%). Time series regression

I am currently working on an industry specific time series analysis of European Equities between 201001 and 201812. I use the European Fama French factor returns (plus the momentum factor return) that ...
1
vote
1answer
96 views

when a co-integrated times series pair has broken the leash

I have two times series, say $T_i$ and $S_i$ over a reasonably large time window, and I have calculated their cointegration (using python's OLS and Adfuller) . Say that the test has passed with high ...
2
votes
0answers
36 views

Problem with Hurst exponent estimation for ARFIMA models

guys. I try to realize my ARFIMA model identification script in R. I try to find the best method for unbiased Hurst exponent estimation (fractional difference parameter could be found as Hurst - 0.5) ...
5
votes
1answer
266 views

Volume or Dollar bars vs. volatility normalized and demeaned financial time series

In his book - Advances in Financial Machine Learning, Marcos Lopez de Prado familiarises the reader with a number of ways of normalizing our financial time series data. Below I provide a couple of ...
8
votes
2answers
920 views

Fitting Copula and Simulation

I would greatly appreciate any insights into the problem described below, regarding using the data obtained from applying the functions of the rugarch package ...
2
votes
0answers
29 views

Tools related to Granger Causality

I would like to know if there are some tools that can measure that one time series is "faster" than the second one. I talk about really similar time series related to high frequency trading (hundreds ...
0
votes
1answer
46 views

serial correlation and CUSUM results

I have the following CUSUM test resulted from autoregressive distributed lag models (ARDL). Does the CUSUM results show that the model is stable? I am a bit confused because the red line in CUSUM ...
1
vote
1answer
96 views

Calculating Ex-ante Sharpe Ratio in multi-period setting

I have built a return process $\{x_t, t = 1,\dots,T\}$ for an asset. Suppose I have generated $K$ sample paths $\{x_t^j, t=1,\dots,T\}, j=1,\dots,K$. I think of two ways to compute the Sharpe ratio. ...
3
votes
3answers
189 views

what are the criteria to select pairs?

I'm new to this forum, this is the first question I posted. I have many candidate pairs and I've used ADF test to make a first selection. There are more than 800 selected. The pairs are absolutely too ...
1
vote
0answers
249 views

R Equilibrium FX using VEC or Behavioural Equilibrium Exchange Rate (BEER)

I dont have much experience with R. I would like to do create model for FX Equlibrium using VEC or BEER. I already know what variables I want to use in model: trade differential between UK and the ...
6
votes
1answer
544 views

What machine learning method is more suitable for prediction of financial time series?

I have time series data for various assets and which I transform to create various features. I have framed the problem as a classification task where I attempt to predict either a positive or negative ...
1
vote
0answers
104 views

Some basic examples for Granger causality

I have two time series, X and Y. The number of observations in each time series is the same and the variables would be price(logged). The goal of my research is to analyze if one variable X follows ...
1
vote
0answers
73 views

Autoregressive Distributed Lag Models (ARDL) results analysis

When using autoregressive distributed lag models (ARDL), I usually get a counter-intuitive result for the selected lag. For example, when examining the relationship between GDP and Foreign Direct ...
45
votes
4answers
5k views

How much data is needed to validate a short-horizon trading strategy?

Suppose one has an idea for a short-horizon trading strategy, which we will define as having an average holding period of under 1 week and a required latency between signal calculation and execution ...
6
votes
0answers
213 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 ...
2
votes
1answer
141 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 ...
3
votes
3answers
260 views

PCA for Risk bucketing

I'm working on a project to justify the use the certain tenors (2y, 5y, 10y, 30y) for risk bucketing. I'm a little stuck after calculating the principal components. Just to describe my approach- a) ...
2
votes
1answer
110 views

How to compute cumulative performance of a portfolio with two equities?

I have a time series of adjusted returns for two companies, A and B. I have created a portfolio consisting of these two time series with equal weighting (sum of weights must equal 1): $w_a = w_b=0.5$...
1
vote
1answer
70 views

Data Sources for Timestamps of Individual Trades [duplicate]

Are there any data sources where I can get the timestamps of individual trades/transactions? I'd like them to be at the second level or even the millisecond/nanosecond level. Ideally, the trades would ...
1
vote
2answers
129 views

Do you optimise models on bootstrapped time series?

As Quants, we soon learn to optimise models, by fitting them to historical time series, e.g. the historical daily returns of some stock. But the historical series of daily returns is just one ...
1
vote
0answers
140 views

What is the best source to get 10 milliseconds time-series data for numerical computation?

I am working with 4th order Runge-Kutta method to compute a second order differential equation. For the best accuracy, I need a 10 milliseconds ohlcv time-series data. I know that I can build it ...
1
vote
1answer
95 views

Calculate New Portfolio Weights Given Today's Returns

I'm looking for a formula to recalculate my portfolio's weights at the end of time $T$, given a vector of the asset weights at $T$ and a vector of returns at $T$. For example: ...
6
votes
1answer
143 views

How to perform cross-sectional asset pricing regression?

I'm wondering is that possible to get insignificant beta estimates in the time-series context, but highly significant risk premium associated with that beta in the cross-sectional regression? Any ...
3
votes
0answers
95 views

Detecting leading stocks using lag correlation

I am working on a project to find leading stocks in a stock market by using lag correlation. Say I want to compare 2 stocks, X and Y, and I have the time series of stock prices. Assume that the ...
1
vote
0answers
33 views

General to specific approach to modelling

I am trying to find the relationship of stock indices across the world. This has been done by the literature, however, I am wondering about the methods chosen. I have decided to go with what I think ...
2
votes
2answers
168 views

remove seasonality in future contracts

very new to commodities. I have raw agriculture future data, and I need to remove the seasonality (de-seasonalize) from the data, what is the general approach ? Thanks for the help!
1
vote
0answers
94 views

How does the FED calculate SAAR for GDP?

In looking at the Fed's GDP growth rate data, it looks like the fed uses a different calculation for calculating annualized growth rate than the typical annualized rate of change. Does anyone have any ...
2
votes
1answer
68 views

Monte Carlo simulations of stock price percentage change rather than stock price

Say we have a stock price time series $S_k$. We can do monte carlo simulations on the stock price to make predictions about future prices (e.g. through Geometric Brownian Motion SDE's). Does it make ...
4
votes
1answer
354 views

Application of ACD models

I have been playing around with autoregressive conditional duration (ACD) models and I have a nicely working R based implementation using real high frequency data (trades only data). However, what's ...
0
votes
0answers
360 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
votes
0answers
271 views

RiskMetrics VAR calculations and conditional distribution of sum of log returns

According to Tsay's book in Chapter 7, for the Risk Metrics model: A nice property of such a special random-walk IGARCH model is that the conditional distribution of a multiperiod return is ...
3
votes
1answer
165 views

Discretizing a Continuous Time Stochastic Volatility Model

How does the discrete time stochastic volatility model arise from the continuous time one? Also, forgive me for cross-posting. I have the following continuous time SDE for a stochastic volatility ...
20
votes
8answers
36k views

How to check if a timeseries is stationary?

I'm using KPSS Method to check if the series is stationary, but I would also like to use another test to confirm if the series is stationary or not, what method coudl I use?
1
vote
0answers
163 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 ...
10
votes
1answer
2k views

ARMA+GARCH prediction with package rugarch (R)

I am analyzing FTSE 100 series, from 2007-01-01 to 2010-12-31 (university exam homework). I have to use the data 'til 2010-11-30 as sample, and the remaining (23) observations as in-sample forecast (...
1
vote
0answers
35 views

Johansen Cointegration Test in R

I know its probably been asked bevor but i just don't get it. I have 2 values (Oil and corn price) and i want to check if they are cointegrated. Bevor that, i have tested if they really are non ...
6
votes
2answers
299 views

Does predictability in a VAR process imply mean reversion or momentum?

There seems to be some disagreement in the literature about this. Define predicability of a stationary series to be $\sigma^2_{t-1} / \sigma^2_t$ Finding mean reverting portfolios using canonical ...
10
votes
0answers
7k views

How to use statsmodels' Granger causality test to measure the lag between two time series?

I am using the Granger causality test to measure the lag between pairs of time series where it is already apparent that one is following the other. So I am not expecting this test to tell me whether ...
4
votes
2answers
177 views

Lagged Residual as Independent Variable

I am building a factor model to estimate future equity returns. I'd like to include an autoregressive residual term in this model. I'd like to have yesterday's error (the difference between yesterday'...
10
votes
1answer
13k views

How to calculate the conditional variance of a time series?

I am reading a paper where the term conditional variance is mentioned, but I am not really sure what is meant by this and how this can be calculated: Fig. 2 shows the conditional variances of the ...
1
vote
0answers
23 views

Sample distribution of cross-sectional statistics of returns

Currently doing an application of VaR on sample of industry portfolios in the US. I have a matrix of $n$ industry portfolios with $m$ time-series observations. I calculate cross-sectionally (for each ...
0
votes
1answer
44 views

Where can I download for free the entire price history of the nasdaq composite and s&p500 indices? [duplicate]

I would like the entire price history of both these indices at an end-of-day level, not intra day. Is there an R api that I can use for such an exercise?
0
votes
0answers
43 views

Interpreting the ACF graph

I am currently struggling with the interpretation of a price chart and the corresponding ACF graph. The question is, if there is momentum in the price of this asset. This is the corresponding price ...
3
votes
1answer
119 views

Asset pricing model factor need to be excess return?

In John Cochrane's Asset Pricing book and his video lecture, he states that asset pricing factors need to be excess returns, a traded portfolio. Is there a reason for that? I can't find explanation ...
0
votes
0answers
59 views

GARCH(1,1) and Value at Risk: Rolling window or non-overlapping samples

Currently studying on financial risk management. I want to test different methods of VaR estimation. I want to model volatility using a GARCH(1,1) model. My question is what should the size of the ...
4
votes
6answers
610 views

Book recommendation for time series analysis

I have been trying to wrap my head around Engel-Granger test and jcitest etc. I have failed thus far. If possible can someone guide me about which books to start with and possibly reach to ...
0
votes
2answers
92 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 ...
25
votes
4answers
14k views

Performance of Open Source Time Series Database for Financial Market Data

We would like to store financial tick data in a database (potentially billions of rows) and then create aggregated (open-high-low-close) bar data from it (e.g. 1min or 5min bars). It was mentioned ...