Questions tagged [time-series]

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

Filter by
Sorted by
Tagged with
2
votes
0answers
54 views

Dividing H in the Hurst power law function to get the Hurst exponent?

For my own learning I have been following the guide here. It is highly instructive. Implementing this in R I was able to reproduce the authors results on the data sets provided within some ...
1
vote
0answers
179 views

Yield curve estimaton using linear regression

Assuming that there are not any zero coupon bonds in the market, then someone has to use the prices of regular bonds with same maturity and characteristics (risk,issue etc.) to obtain the yield curve. ...
5
votes
0answers
1k views

Hasbrouck's information share

Given a cointegrated set of price series, I am trying to compute the Hasbrouck's information share, as described in page 12-13 of this article. page 7-8 of this article I have the vector error ...
8
votes
0answers
179 views

Determining Hurst exponent of a Brownian motion

I am trying to determine the Hurst exponent of a simple Brownian motion, however, I seem to get a result that differs from 0.5. I am following the instructions given on the Wikipedia-page, and here is ...
0
votes
1answer
116 views

Is it possible to generate time&sales(tape) off of the tick data for a stock?

I want to build my own stock trading simulator with the ability to play it faster. ThinkorSwim has onDemand. But it's not fast enough to accumulate more experience. To code up my own market replay ...
5
votes
1answer
852 views

Measuring momentum as AR(1) process

I would like to measure the momentum in the price of a stock from the time the market opens until the time I trade each day. I want to use this momentum number in post-trade analysis (regression of ...
0
votes
3answers
488 views

log return of sp500. Stationary vs strictly stationary

By first glance of this time series; will you say it is stationary? I can easily see some "seasonality" which means that this is not strictly stationary since the distribution will not be the same; ...
2
votes
1answer
183 views

How can I 'quantize' a time-series in 'groups' exhibiting similar patterns? [closed]

In Signal processing, there is a topic of 'Quantization' (the process of mapping input values from a large set to output values in a (countable) smaller set ('states') ). I would like to construct a ...
2
votes
0answers
44 views

Non stationarity issue on copula estimation procedure

In this paper (1), on page 14 (section 4), the author presents an empirical experiment on the computation of a copula through the use of kernels. To do so, he uses the following stochastic process (...
0
votes
1answer
83 views

unsupervised pattern discovery - methods?

Given that I select features manually, what methods are available for pattern discovery with the purpose of time series prediction (footnote)? I only stumbled upon hierarchical clustring ("bottom-up"...
1
vote
0answers
49 views

Minimum Lower Partial Moment (n=2) hedging ratio

I would like to better have understanding on the minimum-LPM hedging. I have understood that the co-LPM matrix cannot be modeled by GARCH type models that are used to estimate to the covariance matrix,...
8
votes
4answers
1k views
2
votes
1answer
563 views

Close and Adjusted Close in Interactive Brokers API and Yahoo Finance

On Interactive Broker's TWS API manual, there are several historical data types to choose from. Which IB TWS data type's Close value corresponds to Close Adjusted ...
1
vote
1answer
134 views

Finding maximum profit on 'ideal' trading with fees

To properly develop my trading strategies I need to find a way to calculate maximum theoretical income made from trading time series with perfect accuracy (i.e. trading while holding 'crystal ball' ...
2
votes
1answer
459 views

Augmented Dickey-Fuller Questions

I've been searching in bibliography about this test applied to an AR(p) model. $$Q(L)(Y_{t})=c+\epsilon_{t}$$ Where L represent the Lag Operator and $Q=1-\phi_{1}x-.....-\phi_{p}x^{p}$ is the ...
1
vote
0answers
53 views

Time series edge minmax probability

Not sure if someone had encountered this problem before: say given a time series, we need to determine the minmax. Usually we need to use some kernel smoother to extract second-derivative. It is easy ...
1
vote
2answers
113 views

Price is Log-normal distributed, yet the return is non-normal

I have a price series. The natural logarithm of the price shows good normality. As shown in the standardized normal probability plot below: However, by viewing the standardized normal probability ...
6
votes
1answer
2k views

Shannon's entropy for financial times-series (return)

I'm looking at Shannon entropy, and generaly at ways to tell noise from signal when observing intraday returns (at the minute level for now). In python, e.g. I've implemented the fomula (sum of P(xi)*...
2
votes
0answers
63 views

Determine GARCH(1,1) from a mean reverting time series recursion

Let $(v_t)$ be a discrete time series of variance obeying a mean-reverting variance process $v_t$, which is actually the discrete version of the Heston model in finance. \begin{align} x_t &= \sqrt{...
0
votes
0answers
359 views

Interpreting ACF/PACF of return series

Researching a return series on some currency pairs I grabbed 2 years worth of daily data and got to work trying to fit an ARIMA/GARCH model to it. Fitting the (log) return series: ...
4
votes
1answer
216 views

R Calculate future price range and plot the result

First I want to say that I've read this post (How to calculate future distribution of price using volatility?) but it doesn't help much. Here is what I'm trying to do (values are not real) Let's ...
1
vote
2answers
219 views

Log-periodic power law model: is it a continuous or discrete-time process?

Are the log-periodic power law models used to predict financial market crashes continuous or discrete-time processes?
4
votes
2answers
325 views

Fractional Brownian motion - probability density function of the increments

I'm starting investigating the properties of the fractionally integrated brownian motion, yet I'm not able to figure out what kind of distribution should an increment of a fBM process follow, ...
2
votes
1answer
306 views

R Mean Reversion Estimate on Funds

I am new to mean reversion, and I'd like to run an analysis on a fund (ts with monthly returns only) to see if mean reversion applies and if so, when it will happen. Most of the examples I found ...
0
votes
1answer
296 views

Estimate an AR(1) model from returns [closed]

I am studying share price log returns and AR(1) model. I downloaded data from $FTSE100$ and I used the Adj.close column to find the Ln returns: Now I am trying to understand how can I estimate an AR(...
1
vote
0answers
59 views

Creating a synthetic future

Let's say we have a time series for an illiquid future and we would like to replicate this time series using two time series for liquid futures using daily rebalancing. What would be a good approach ...
16
votes
5answers
3k views

Are two identical time series cointegrated?

I did cointegration test on two identical time series, and the result shows that they are not cointegrated, but intuitively, I think they are. Can anyone share some thoughts on this? Thanks!
1
vote
3answers
2k views

How to convert weekly data to monthly in r (or in Julia)

I have weekly series on financial risk index data as follows: DATE NFCIRISK 1/8/1971 0.58 1/15/1971 0.61 ......through 10/6/2017 -0.88 10/13/2017 -0.89 10/20/2017 -0.89 ...
1
vote
0answers
134 views

ARMA-GARCH Forecasting [closed]

I want to forecast a differenced time series of an Index using the combined ARMA-GARCH model (because I want to forecast the mean and not the variance). My model is a ARMA(2,2)-GARCH(1,1) model. So ...
-1
votes
1answer
470 views

How to use exponential smoothing for trading?

I was wondering if there's a rule of thumb regarding the value of alpha used when performing exponential smoothing. I plan to use this technique to preprocess my data before feeding them into my ...
1
vote
1answer
100 views

Why should we care if the “squares of returns are independently distributed over time” to choose an adequate model of the distribution of returns?

In a Time Series Book by Hashem Pesaran, he mentions that there are a number of issues that need to be addressed in order to choose an adequate model for predicting asset returns. I understand the ...
-1
votes
1answer
709 views

Where to find historical fundamental data of S&P constituents in Thomson Reuters database?

I need data such as Net Income, ROA, ROE, etc. for companies in S&P 500 Index. I would like to see the values also for other years, e.g., since 2010. However, when I log-in to Thomson Reuters ...
2
votes
0answers
203 views

Trouble computing the VaR for Student's t-distribution for a minimum-variance portfolio composed of four cryptocurrencies (BTC, ETH, LTC, and XMR)

I have modelled the time-series of daily log-returns from August 2015 to October 2017 of a minimum-variance portfolio composed of four cryptocurrencies (BTC, ETH, LTC, XMR) by fitting the data to four ...
8
votes
3answers
880 views

Is the average of independent Brownian Motions still a Brownian Motion?

If $W$ and $B$ are independent Brownian Motions (BM thereafter), then the average of $W$ and $B$ is $X_t=\frac{1}{2}(W_t+B_t)$. Where do I begin to show that indeed it is still a BM? Also, if both ...
2
votes
0answers
112 views

What is a good algorithm to predict volatility in metals commodity markets? [closed]

I'm trying to create a script to predict major swings in the price of Aluminium. I am trying to implement a dynamic time warping algorithm for the same. Was wondering if this really is the best ...
-1
votes
2answers
857 views

adding dummy variable to ts object in r for particular quarter

I've looked all over and can't seem to get a clear idea of how to do this; I have ts data with quarterly frequencies. I simply want to add a dummy variable only for the data corresponding to Q4 but I ...
3
votes
2answers
1k views

Choosing the right statistical test for Mutual Fund Performance Evaluation

How do you suggest I do this? I would like to perform a statistical test to check if: the aggregate alpha of all funds equals 0. the aggregate beta of all funds equals 1. Data Sample of 1000 ...
1
vote
1answer
828 views

Online algorithm for calculating EWMA at irregular intervals?

What is a fast online algorithm for calculating the EWMA (exponentially weighted moving average) of an input variable observed at irregular intervals? I know the formula for when sampling at regular ...
1
vote
1answer
68 views

which method is the roubust method to estimate the Hurst parameter?

I know there exist lots of method to estimate the Hurst parameter, such as R/S, V/S, GHE, DFA, DMA, Wavelet Spectral Density, Whittle and so on. Can you tell me which one is the best one. Is anyone ...
4
votes
0answers
751 views

Application of time series analysis to Bitcoin prices [closed]

Various exchanges allow for the trading of Bitcoins. The price of Bitcoin was very volatile since the inception of the system, today it is 391.76 USD: I wonder whether time series analysis tools from ...
4
votes
6answers
15k views

Which library shall I use for time series analysis in Java?

I'm looking for a library to do some time series analysis in Java but I can't find anything suitable. I've found plenty of libraries such as Math3 of JSAT but there's much I can you for my problem. ...
0
votes
1answer
48 views

Is my data fittet to be significant?

I am new to this forum and hope for some help. I have a dataset of returns. I cannot tell where these come from, but let's assume they come from a trading algorithm of stock prices. The returns are ...
1
vote
1answer
654 views

principal component analysis on non stationary data

I read that since stock prices are non-stationary it does not make sense to take their covariance. So I took the log returns of stocks, computed covariance matrix, took the top few eigen vectors that ...
-1
votes
1answer
78 views

VaR estimation when returns are not independent, e.g. ARCH

Time series of returns, $r_t$, in finance are often modeled with some type of conditional heteroskedasticity model, e.g. ARCH(1): $$r_t = \sigma_t z_t$$ $$\sigma_t^2 = a_0 +a_1 r_{t-1}^2$$ where, ...
1
vote
1answer
478 views

How to know if a time series is trending or mean reverting?

I came across Michael Halls-Moore article on using the Hurst exponent test to determine if a price time-series is mean-reverting, trend-following or closer to a random walk, but doesn't this disregard ...
4
votes
3answers
2k views

Calibration of a GBM - what should dt be?

I have a time series of daily data that I want to calibrate GBM parameters $\mu$ and $\sigma$ to. Using the discretized solution $$ S_{t_{i+1}} = S_{t_i}\exp\left(\left(\mu - \frac{\sigma^2}{2}\...
1
vote
1answer
100 views

How to find coefficient that will minimize the distance between few times series

I have 3 time series X1, X2, X3. I want to find the coefficient (c1, c2) that will minimize the distance between them as follow: $$MIN\sum\sqrt{(X1-(c1*X2+c2*X3))^2}$$ The constrains are: $$-1< ...
1
vote
3answers
177 views

Hourly Returns Statistical test

I am trying to do an analysis on time zones effect on intraday returns. As a first step, I collected hourly log returns for the past 3 years and bucketed them by hour (so that I have 24 buckets ...
1
vote
0answers
123 views

Testing whether a process is a Wiener process [closed]

Ideally I would like links to code implementations (eg. Matlab ) or book/paper references, but I would appreciate suggestions on various methods. Update: I was hoping to attract people who test the ...
2
votes
1answer
192 views

Looking at distribution of yearly returns of time series

For S&P, or any time series for that matter. When doing analysis on the distribution of the yearly returns, should I be looking at 1) the daily year over year values, 2) pick some starting point ...