# Tagged Questions

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

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### Is it too important that my residuals be normal? I am Using an ARMA/GARCH model

I am trying to fit an ARMA/GARCH model to a time series. I found that the best candidate is an ARMA(1,0) + GARCH(1,1) with gaussian white noise It has coefficients with p-values near cero and the ...
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### Logistic Regression of tick data

I've been given some data (it's financial tick data) and I want to predict based on some observed variables whether the next move will be up, down or unchanged. So I have been trying to use ...
487 views

### Alternative ways to understand time-varying comovement between two time-series?

I have been looking into ways to better understand how the dependencies/correlations/etc between two time series can vary over time. I first thought about using a Kalman/particle filter over a ...
217 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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### Comparing volatility using GARCH

Hi, I am investigating if the policy of inflation targeting lowers the volatility of inflation. I have ran the GARCH regression: Inflation(t) = C + Inflation(t-1) + Inflation(t-2) + Error, but ...
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### Calculating the volatility for Black Scholes

The following problem is from the book by Hull. I did it but I am not sure it is right. I am hoping that somebody here can tell me if I did it right and if not where I went wrong. Thanks Bob ...
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### How do I change the date format in a dataframe column. [migrated]

I have a column in a DataFrame with dates in yyyymmdd format and I need to change it permanently to yyyy-mm-dd. How can I do that?
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### 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 ...
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### algorithmic trading strategy based on HHT

I would like to create some trading strategy based on the HHT or at least to try to do some analysis using this method. I read the article wrote by Huang at al. and gained some underesting of the ...
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### How to estimate variance-covariance matrix of assets with different length of historical data? [duplicate]

Consider you have 4 assets A, B, C and D, where Asset ...
137 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 ...
123 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 ...
173 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 ...
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### 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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### 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)) ...
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### 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 $N(0,1)$. Assuming the ...
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### 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 ...
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### 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 ...
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### 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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### 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 ...
87 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 ...
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### 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 ...
1k views

What are the most common ways to model intraday trading volume, particularly for futures contracts? There are obviously a number of seasonal-type factors, like roll, economic news releases, time of ...
206 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 ...
3k views

### Is R being replaced by Python at quant desks?

I know the title sounds a little extreme but I wonder whether R is phased out by a lot of quant desks at sell side banks as well as hedge funds in favor of Python. I get the impression that with ...
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### 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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### 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 ...
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### 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 ...
136 views

### Filtering out AR(1) effects before using stochastic volatility model

I wonder if I first filter out AR(1) (autoregressive model with lag 1) effects from univariate time series and then fit stochastic volatility model does above procedure introduce any bias at first or ...
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### 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.
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### 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 ...
299 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 ...
350 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 ...
162 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 ...
265 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 ...
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### 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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### 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? ...
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### 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. ...
76 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 ...
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### 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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### 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 ...
390 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 ...
187 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 ...
232 views

### Unsmoothing of returns

The following problem arises in the context of private equity, which typically report "smoothed" returns (think of it as a moving average). As you can imagine, "smoothed" returns would have a much ...
6k views

### What is a stationary process?

How do you explain what a stationary process is? In the first place, what is meant by process, and then what does the process have to be like so it can be called stationary?
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### 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 ...
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### 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 ...
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### How is stock data objectively different to this random walk?

I have a random walk that is generated as so using python, numpy, and matplotlib ...