Questions tagged [time-series]

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

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32 views

Difference between Predicting stock returns and Forecasting stock Returns?

The data that is used are either Technical Indicators, Fundamentals Indicators or Macro Indicators which is time series in nature. Given, if we are estimating one-period ahead returns(t+1), is there a ...
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How to implement Time varying EWMA cross correlation in STATA?

I have read this question, I know about lambda, demeaned subindexes. But not able to implement in STATA?
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Bloomberg tick data timezone offset because mismatch in bloomberg api and excel bloomberg

i am trying to fetch intraday tick data for security->C Z9 COMB Comdty,startdatetime:2019-08-05 15:30:00 Enddatetime:2019-08-05 15:35:00 from excel and bloomberg Api but response is mismatching can ...
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2answers
123 views

Absorption Ratio

I'm actually trying to implement Mark Kritzman's absorption ratio (Principal Components as a Measure of Systemic Risk by Kritzmam, Li, Page and Rigobon, 2010, SSRN 1633027) using Python, but I'm not ...
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43 views

modelling known regime shifts

I wish to model a price time series with a known regime shift: electricity price before during and after the introduction of a carbon price. The time series looks like this: you can see the jump in ...
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1answer
54 views

Can MACD be calculated for values other than 12 and 26?

I am working on time-series classification problem using Convolutional Neural Networks in Python. The data-set used is financial stock market data (like yahoo finance). I am using some technical ...
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2answers
100 views

Why do we need event-driven backtesters?

I am reading this article at quantstart regarding event-driven backtesters. It seems to me that the main advantage of using an event-driven backtesters is that it avoids look-ahead bias. Usually I ...
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1answer
79 views

Trading 3 stocks X Y Z where X cointegrated to Y, Y to Z, but no other cointegration is available

Suppose you have 3 stocks, say X Y Z. You also know that X is cointegrated to Y using some test (say ADF) and Y is cointegrated to Z. However, no transitivity, and no threesome cointegration ...
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91 views

How to handle Holidays in Time-Series Datasets?

Im currently analyzing a Dataset of the German Stock market. While Holidays like Christmas or New Year aren't a problem for Return Calculation or Portfolio Performance, im testing some regressions and ...
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1answer
72 views

What does A(B) mean in time series

So I have been reading some papers regarding time series, mainly from Granger and Engle. I am a bachelor econometrics student, but I have never seen such notation before. For example, A(B)(1-B)x(t) = -...
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75 views

Fama French Three Factor Model: How do I get the risk premia?

I try to calculate the cost of equity with the FF3 model and already estimated the beta factors for the market, size and value risk premia by using regressions and the data provided on the Kenneth ...
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1answer
64 views

generalisation of cointegrated stock pair strategies to multiple cointegration

Question: as it is well known, there are strategies to trade pairs of stocks which are known to be co-integrated. See for instance here: https://medium.com/auquan/pairs-trading-data-science-...
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54 views

Cross Effect in OLS

I am using cross effect in OLS regression for a time series problem for a multivariate regression. I want to quote reference for use of cross effect. Secondly, I want to explain why better to use ...
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1answer
90 views

How can stationary time series data be used as input in an ML model?

I am halfway through "Advances in Financial Machine Learning" by Marcos Lopez de Prado. I understand that a time series like stock prices can be transformed to make it sufficiently stationary. ...
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1answer
79 views

Exponential Smoothing - Alpha greater than 1

Simple stats question. I'm having trouble finding anything in the literature as to why the smoothing coefficient can never be greater than 1. This question was started by me doing time series ARIMA ...
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86 views

linear model of price changes

I came across the below equation for linear model of price changes in E.Chan book Algorithmic Trading which is the base for a strategy. ...
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41 views

Brownian motion from price-series, what is the time step?

If I assume a given empirical price-series is a brownian motion, I can estimate the drift and standard deviation as long as I know what the time step was when the process was 'generated'. But since ...
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1answer
63 views

Forecasting a seasonal series with R

I am working with the program "R". I used the command "seas (X-13)" to deseasonalize my quarterly series, then I did the forecast with it. Therefore my forecast is in deseasonalized terms. Now, I was ...
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20 views

Pricing a transfer option for oil

Need some input in how to attack this problem. Given are 8 timeseries: UK Oil price, Delivery Quarter 1 2020 UK Oil price, Delivery Quarter 2 2020 UK Oil price, Delivery Quarter 3 2020 UK Oil price, ...
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49 views

Log transformation of TS-stationary time series

I usually see the $log$ transformation of prices: $$p_{new}\left(t\right) = ln\left(\frac{p_t}{p_{t-1}}\right), t \in [2...N]$$. Let's our series be a trend stationary time series like: $$p\left(t\...
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46 views

Is this a good (partial) autocorrelation or bad?

I was playing with some data on deviation of close prices from its smoothed estimated and got these ACF and partial ACFs: I still struggle to get proper intuition to the ACF plots. What do the plots ...
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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 ...
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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 ...
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1answer
93 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 ...
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35 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) ...
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27 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 ...
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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 ...
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1answer
66 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. ...
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151 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 ...
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86 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 ...
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1answer
74 views

Is there such a thing as resonance in economic underliers?

In physics the occurence of resonance is explained and widely understood in its linear form and subject to research in nonlinear resonance. Example for instance are resonant frequencies of objects. ...
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72 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 ...
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1answer
154 views

Multivariate Markov Regime switching GARCH

I have a regression with 4 independent variables and a dependent variable. I want to implement a Regime switching GARCH model but have been unable to find a package in R,Python or Matlab. MSGARCH ...
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161 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 ...
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84 views

Standard GARCH(1,1) model with external regressors

I have a queastion how does a standard GARCH(1,1) model with external regressors in mean and variance euqations look like ? I know that standard GARCH(1,1) model without external regressors has the ...
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3answers
222 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) ...
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1answer
97 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): $w_a = w_b=0.5$...
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1answer
66 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 ...
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32 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 ...
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93 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 ...
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1answer
135 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 ...
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139 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 ...
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80 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 ...
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1answer
67 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 ...
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244 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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1answer
147 views

Can you use GARCH-MIDAS for intraday data?

I'm working on a project to forecast volatility and I'm using intraday data (1 min). I want to include exogenous variables to the model that have daily frequency. I was wondering if GARCH-MIDAS can be ...
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2answers
123 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 ...
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170 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 ...
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86 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: ...
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145 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 ...