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

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3answers
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1answer
219 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 ...
1
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0answers
111 views

Application of time series analysis to Bitcoin prices

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 ...
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0answers
51 views

state space for affine yield curve

i would like to reproduce in R the working paper " Affine free arbitrage class of Nelson Siegel term structure". The authors considering the equation of nelson siegel plus an adjustment term(C(t,T)) ...
3
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0answers
80 views

Fourth moment of ARCH(2)

I am studying the ARCH(2) process given by $$X_t = \sqrt{h_t} \varepsilon_t$$ where $$h_t = \alpha_0 + \alpha_1 X_{t-1} ^2 + \alpha_2 X_{t-2} ^2$$ and $\varepsilon_t$ follows $N(0,1)$. ...
2
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1answer
77 views

Define polynomials of an ARMA process

I just started out with financial time series and I'm a bit stuck with ARMA models. I have the following ARMA process: $-4X_t + X_{t-2} = Z_t + 0.2 Z_{t-1}$ Now I am being asked for the polynomials ...
2
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2answers
85 views

Is there an implementation of VAR-EGARCH model in R or Stata?

I am writing my undergrad honor thesis and want to run a multivariable VAR-EGARCH model. Is there any package in R or formulas in Stata 14 that allows me to implement directly? If not, could you ...
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2answers
133 views

What methods are there for showing a time series is mean reverting?

What methods are there for showing a time series is mean reverting? Is there a hypothesis relating to the Ornstein-Uhlenbeck process for example?
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1answer
123 views

Building predictive model for closing price using only previous days data

I am trying to determine which quantitative model to try and build a predictive model for the next day's closing price for all the S&P stocks based on their bar for that particular day. However, I ...
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0answers
50 views

Transforming Variables in time series regression

I have multiple quarterly time series data and trying to build a linear regression model using this dataset. Should the transformations on the LHS and RHS be the same i.e QoQ percent changes? Could ...
7
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0answers
156 views

Imposing Restrictions on Cointegrating Vectors, R example

The code given below estimates a VEC model with 4 cointegrating vectors. It is a reproducible code, so just copy and paste into your R console (or script editor). ...
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2answers
206 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 ...
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2answers
245 views

How to trade a Ratio?

I came across a ratio plotting of Corn And Soybeans contracts, notice it's in a historical low, an intuitive question came to my mind, how should I trade this ratio (or relationship)? It's unlike flat ...
4
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1answer
85 views

What is the variance risk premium?

Can someone provide an intuitive understanding of the variance risk premium? I am very confused by this definition and cannot interpret my time series analysis.
8
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3answers
365 views

Does Kalman filter always improve over linear regression?

If I have a simple linear regression that has statistical signification but I would like to improve the overall prediction results. Will a Kalman filter be always an improvement or as least achieve ...
3
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1answer
98 views

volume-returns cross correlation interpretation

I want to find the relationship between volume and price returns in the S&P500. My first thought was to run a cross correlation in order to find who leads and who lags in the relation. It´s my ...
4
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0answers
274 views

How to forecast high-frequency data?

Introduction: I have seen a plenty of articles/books regarding volatility forecasting applied to high frequency data, but none of them were dedicated to forecasting the actual prices (for example ...
6
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1answer
303 views

How to use physics models in Time Series Analysis and Forecasting.

I have been studying methods of Technical Analysis for several years and I am disappointed. I actually do not consider it useful. I have not met anyone who can constantly win in the market using these ...
6
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2answers
1k 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 ...
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0answers
47 views

labeling high frequency signal data

Was curious if anyone has methodologies they can recommend for systematically labeling (discrete) signals generated from intraday tick data for use in classification or detection models ?
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4answers
687 views

Thesis using Momentum strategies in R, tips on good books, guidelines etc on how to do the programming?

I am quite new to R and will be doing an empirical analysis of momentum strategies in R using a dataset from the index OSEAX from 1980 to 2014. The momentum strategy will for the most part resemble ...
5
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1answer
221 views

Up and Down days in GBPUSD and a Filter

I want to study if the odds of an up or down day in a forex pairs is 50-50. I just count the total number of up and down days in X years and compare it with the total days. The results are very ...
2
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0answers
31 views

Specifying integration level of time series [closed]

Following model was estimated on 200 observations. How to specify the level of integration of $X_t?$ In brackets there are standard errors and p-value of Breusch-Godfrey test is also shown. ...
3
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2answers
219 views

Relationships between white noise and random walk

I would like to ask 5 questions about relations between these processes. 1) Could white noise be also a random walk? 2) Could random walk be also a white noise? 3) Could white noise be stationary? ...
2
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1answer
104 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 ...
2
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1answer
272 views

2-step estimation of DCC GARCH model in Python

Embedded in this thread are multiple questions. I'm currently im the process of implementing a DCC GARCH forecast model on quantopian (a python-powered trading platform). The two step consists of ...
3
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1answer
66 views

Return.portfolio error from PerformanceAnalytics package

When using the PerformanceAnalytics package of R, I am getting an error from the Return.portfolio function whenever I ask it to rebalance_on any frequency. If the rebalance parameter is removed, the ...
4
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1answer
336 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 ...
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1answer
266 views

predict next day's close price using hmm

I am reading this paper(Stock market forecasting using hidden Markov model: a new approach) and get confused about how they predict the next day's close price. Below is what the authors say about how ...
6
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2answers
399 views

Value at Risk for Futures Contracts

I would like to know how you would compute Value at Risk on a portfolio of futures i.e rates futures, commodity futures and equity. How do you deal with the discontinuous form of commodity futures for ...
3
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1answer
74 views

compute technical indicators from candle data

i have a rookie question but can't find the answer anywhere so..what is the right way to compute a simple moving average when you have an array of (open,close,low,high) tuples ? From what i saw so ...
2
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1answer
95 views

Garch models and assumption of stationarity ?

I found big inconsistency in the GARCH models and their underlying assumption of stationarity. GARCH models require that data must be stationary, where stationary means both mean and variance are ...
2
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1answer
101 views

FORECASTING Model AR(1) in an Autoregressive Form The Pi´s Parameters

Ive been implementing a little exercise to obtain the first 2 forecasting points of an AR(1) process. And i want to have the forecasting ponts using the three forms: Im folowing this pdf ...
6
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2answers
247 views

Is there any research on pyramiding techniques of entering/exiting a trend?

I am looking for any research about optimal strategies for gradually building (scaling in) positions inside a trend as well as optimal gradual exit strategies on pullbacks/reversals to minimise ...
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1answer
62 views

Does it make sense to interpret autocorrelation and box test on 5 data points?

I am trying to see if after I trade a stock the price movements at 2, 5, 7, 10, 30 and 60 seconds after exhibit any autocorrelation. Below I have the returns from my trade price to the trade 2,5,7,10 ...
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0answers
225 views

Markov-Switching Multifractal and FX Rates

Is there a better model than Markov-Switching Multifractal (MSM) for detecting regime shifts in FX rates across multiple time horizons? I am especially interested in the different aspects of the ...
2
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0answers
112 views

Identifiability of a state space model (Dynamic Linear Model)

Take a general linear Gaussian state space model (SSM)(aka Dynamic Linear Model DLM): $X_{t+1}=FX_t + V_t$ $Y=HX_t+W_t$ $V_t \sim N(0,Q)$ $W_t \sim N(0,R)$ I am interested in the ...
2
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1answer
84 views

How to construct a cointegrating vector using more than 2 price series in R?

I use now this code from hier Why does the following data fail my cointegration test? with slightly modification of possibility to load something directly from Dropbox file storage . ...
10
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2answers
424 views

GARCH model, expectation of volatility?

Consider a time series $\{r_t\}$ following a standard GARCH(1,1) model, i.e., $$ r_t = \sigma_t \epsilon_t,$$ where $\epsilon_t \sim N(0,1)$ and are i.i.d, and $$\sigma_t^2 = \omega + \alpha_1 ...
2
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1answer
98 views

Estimating correlation using EWMA

I am using an EWMA model to evaluate the correlation between yearly time series. I know Riskmetrics uses $\lambda=0.94$ for daily data and $\lambda=0.97$ for monthly data. Is there a value ...
3
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1answer
132 views

Applying Time Delay Neural Network to financial events

I have an IT background and I would like to use data from a forex calendar like this one to predict prices. The problem is that calendar news impacts can last for days or weeks or even can effect ...
3
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1answer
163 views

What is the best data structure/implementation for representing a time series in C#?

I'm looking for a tick by tick high performance container. So far I've been using List where Tick is a simple struct with a DateTime and double field. I'm using Linq for date lookups but it's ...
2
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2answers
1k views

Speed of mean reversion of an interest rate model

I would like to have a bit more of intuition about the concept of "speed of mean reversion" for an interest rate model, e.g. Vasicek or CIR. In particular, is a negative speed of mean reversion ...
3
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1answer
104 views

Accuracy of GARCH& ARCH forecast

I'm learing ARCH&GARCH model. I have four questions that I don't know the answers 1st: ARCH & GARCH are often used to evaluate equities. Does it mean that ARCH and GARCH are fitter for high ...
2
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2answers
167 views

Extracting Signal from Noisy Data

Consider a scenario in which Y_t represents the % change in price and we want to use X_t to predict Y_t. We assume that X_t is information we get before Y_t is revealed. Suppose that in reality Y_t ...
4
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2answers
89 views

Does heteroskedasticity of returns depend on the time frame?

Similarly to my last question, for which I obtained very interesting and useful answers, I would like to know if there has been any study regarding heteroskedasticity and time-frames of the returns. ...
5
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2answers
121 views

Is there a relation between these two forecasting/estimation approaches?

When learning econometrics I have usually seen stuff from the following perspective: Assume $Y_t = f(X_t) + e_t$, where f is some function of $X_t$ (typically linear). For example, assume $Y_t = X_t ...
5
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2answers
133 views

Interpretation of Correlation

I have two geometric Brownian motions (GBMs) driven by the same underlying Brownin motion, namely \begin{align*} S_t^1 = S_0^1\exp\left(\left(\mu_1 - \frac{\sigma_1^2}{2}\right)t + \sigma_1 ...
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2answers
563 views

Bloomberg tick data timezone offset

I am using python to access the Bloomberg Desktop API and am running into issues with the timezone conversion for their tick data. The data they deliver is supposed to be UTC but there is something ...
0
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0answers
33 views

johansen cointegration test eviews interpreation

I am not sure whether i am interpreting the cointegration test correct. This is the test result : Because of the probability of the test i understand that my series are cointegrated of order 2. ...