The study of the collection, organization, analysis, and interpretation of data. Questions may deal with descriptive statistics, probability distributions, random variables, sampling, regression, density estimation, filtering, inference, estimation theory, or computational statistics.

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3
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3answers
252 views

References on Statistical Arbitrages

Is there any basic materials (books, papers) to read on Statistical Arbitrage? I certainly understand much of the useful information is in the industry. I just want to get some understanding on the ...
0
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0answers
19 views

Value of sequential mutually-exclusive options (A variant on the Secretary Problem)

How much should you offer a potential hire in a signing bonus? Imagine you are interviewing a list of candidates for a particular job. Each candidate has a "lifetime value", and probability of ...
3
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1answer
226 views

rollapply with Arima model: testing for stability of coefficients

I am trying to fit an arima model on a rolling window using rollapply.My aim is to plot a graph of the evolution of the coefficient, plot the error and the standard deviation. well i encountered the ...
1
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0answers
91 views

Create Markets Bubble Indicator

I am trying to replicate a Bubble Indicator described here. The indicator is strictly based on calculating the regularity of price behavior to determine herding in multiple time frames. I tried the ...
2
votes
1answer
108 views

How to account for correlation between strategies when they are added linearly?

There are n strategies which are going to be combined linearly. Using a pre-exisiting model I get a set of n weights which will be used to combine the strategies. But the model does not take ...
2
votes
1answer
451 views

using garch to forecast volatility but getting low persistence model

I am using a GARCH(1, 1) model to try model volatility for a certain stock. I have a GARCH function in matlab that returns the three parameters, omega, alpha & beta. I then use this parameters ...
2
votes
3answers
488 views

Dou you have an example of implementing Engle-Granger 2-step cointegration?

Does anyone know where to find an example of implementing Engle-Granger 2-step cointegration? Python's ideal, but any language will do. I've skimmed and read many articles, but understand little ...
1
vote
1answer
105 views

To lump or not to lump

Suppose I have a very simple asset whose price takes only three possible values: $X_t\in \{-1,0,1\}$. I also got some discrete time series $X = (X_t)_{t\geq 0}$ and I would like to come up with a ...
1
vote
1answer
165 views

What is an appropriate algorithm to use for tax loss harvesting?

I've been reading into how Betterment and Wealthfront have architected their tax loss harvesting algorithms, but they stop short of providing any real examples. Essentially, they both reduce to: ...
2
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0answers
27 views

What methods - inspired by Haavelmo’s Structural Econometrics - can show that a partial equilibrium model is unreliable? [closed]

According to Spanos 2014 Revisiting Haavelmo's Structural econometrics: Bridging the gap between theory and data Dynamic Stochastic General Equilibrium models are statistically inadequate, in such an ...
8
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3answers
5k views

Can the Hurst exponent be greater than one?

Can the Hurst exponent be greater than one? Does it mean that the time series follows a random walk or that it's not stationary?
2
votes
1answer
103 views

Law of large numbers necessary for APT derivation?

The question refers to the well-known Ross (1976) paper with the derivation of the Asset Pricing Theory. In the APT, the return of asset $i$ is driven by a linear factor model: $$ R_i = \alpha_i + ...
3
votes
1answer
287 views

Bayesian or Frequentist in Finance?

I'm currently an undergrad at a Canadian university and our finance courses has been brought up through the frequentist approach (ols, hypothesis testing, sampling theory). Only recently, through ...
-1
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1answer
153 views

Probability distribution and Stock Price Movement [closed]

How can we use normal distribution for finding the probability of a stock price offer where current price offer depends upon the last price offer. The price offer on some day can go 10% above (at the ...
3
votes
1answer
310 views

Stress Testing Methods

I'm working on the following task: Given quarterly data: a time series representing the 1-year realized (10 years of data) rates of default on a portfolio of mortgages a slew of ...
3
votes
3answers
13k views

Kalman Filter Equity Example

I am looking out for some material where I can study about Kalman Filter applied to Equity using Excel or R?
6
votes
4answers
591 views

What are the canonical books for statistics applied to finance?

I have some decent knowledge of probability, stochastic processes and option theory, however I do not have a proper background in statistics. Now I am working quite a lot with data, and trying ...
20
votes
6answers
8k views

What is the intuition behind cointegration?

What is the intuition behind cointegration? What does the Dickey-Fuller test do to test for it? Ideally, a non-technical explanation would be appreciated. Say you need to explain it to an investor ...
1
vote
0answers
269 views

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

I have some time series from a stock exchange market. For each of them, I want to answer the question that whether the price will grow at least p percent in the d coming days or NOT(and during these ...
2
votes
0answers
83 views

seasonality and generalized additive model

I am reading a report which talks about seasonality. There is a chart showing the average returns for each month of the year. In the chart it appears the last 3 months of the year tend to be negative. ...
1
vote
1answer
531 views

detecting and measuring lead lag effect

Given two time series data. I remember there is one statistics that tells you one is the leading factor while the other is the lagging factor. However, i do not remember the exact details. correlation ...
4
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1answer
284 views

factor models and using cross section regression

I have been doing some reading on factor models. In the literature it mentions that when creating a portfolio that maximises particular attributes it may lead to unwanted bias to other factors. I ...
10
votes
3answers
2k views

Hidden Markov Model & Its Application

I have started reading about HMM it gives an intuitive idea about what HMM is all about. I am looking out for example where its applied to Equity model using R / Excel. The material which I read so ...
4
votes
2answers
273 views

Predict Futures Prices based on weather + agricultural data

I’m working in the area of Data Mining and have come up with the following idea for my Masters project.The text may not be the best structured but it’s a working draft to give you a quick idea. ...
2
votes
2answers
75 views

Is this a reasonable approach to determine the relative importance of valuation factors?

I am trying to come up with a measure of relative importance of a number of valuation factors. I am wondering whether correlation coefficients can't be used for determining this. More on the issue: ...
1
vote
2answers
341 views

How to combine Gaussian marginals with Gaussian copula to obtain multivariate normals?

in the book "Numerical Methods and Optimization in Finance" I red the following: "Combining the Gaussian copula with Gaussian marginal gives a fancy way of expressing multivariate normals. However, ...
3
votes
3answers
410 views

Measuring historical earnings surprises, their frequency and severity

This is my first post to Quantitative Finance, so I hope my question is formatted the right way. I am starting to research the effects of earnings surprises on certain equity indices. Is there a ...
3
votes
0answers
117 views

State Space models with Short Time Series

My problem is that I have a state space model that I estimate using the Berndt–Hall–Hall–Hausman (BHHH) algorithm. The state space model is relatively simple in that the hidden part follows a pure ...
1
vote
0answers
58 views

How to value a portfolio of non-mature consumer loans?

I'm looking for the best way to value a portfolio of consumer loans that have NOT reached maturity and for which I do observe the payment/default history to date? I'm working with a large database of ...
1
vote
0answers
368 views

Autoregressive distributed lag models ADL(p,q) howto in preferably matlab (stata/R/python/C# etc)

Could anyone provide me the details of how to determine the lag order of the distributed lags for an ADL(p,q) model in Matlab or another statistical package (and very much preferably in combination ...
0
votes
1answer
211 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 ...
3
votes
1answer
87 views

Properties of a Symmetric Copula

I am working with the following copula, and have a few questions about it: $C(x,y) = xy + \theta (1-x)(1-y)xy$ Here $\theta \in [-1,1]$ and $x,y \in [0,1]$ First, I am trying to show this copula is ...
6
votes
2answers
384 views

Why are we obsessed over normalizing financial data?

I have recently began work on some high frequency financial tick data. I have been told to 'normalize' the data as much as possible and run linear regressions through them. In fact, the data doesn't ...
2
votes
2answers
172 views

What are the proper metrics to look at for checking discrepancies in these two time series

I am obtaining bid/ask price and volume market data from two different sources for the same ticker and for the same day and checking to see that at time intervals X they are "roughly the same". The ...
0
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2answers
198 views

Use of geometric mean for average return of several indices

Can anyone give any reference for using the geometric mean to average the returns from several indices? Note, this question is not about the usual use of geometric mean to obtain the average return ...
7
votes
2answers
467 views

Efficiency vs. Robustness - To use a constant or not in single factor time-series regression?

Arbitrage pricing theory states that expected returns for a security are linear combination of exposures to risk factors and the returns on these risk factors. Betas, or the exposures of the security ...
9
votes
4answers
1k views

Why shrink the covariance matrix?

I'm trying to understand why it's useful to shrink the covariance matrix for portfolio construction or in fact general. Think I missing something. I know if you have 5,000 stocks it's a lot of ...
1
vote
3answers
2k views

Calculate correlation between two sub portfolios and the combined portfolio

I have two sub portfolios (lets call them portfolio a & portfolio b - a portfolio is just a vector of weights that sum to 1) that combine to create a total portfolio. I also have a 2 x 2 ...
6
votes
2answers
297 views

Why do I have a statistically significant slope regressing R(t) on R(t-1)

I am reading Cochrane's lecture note here He mentioned that when you regress annual return on time t on that of time t-1, you will have neither statistically significant nor economically significant ...
3
votes
1answer
418 views

a good book on option pricing from theoretical and practical aspect

This is the situation someone I know is in: She has good understandings of stochastic calculus and the very basics about black-scholes and binomial model, but nothing more. Her background is in ...
2
votes
1answer
339 views

How to compare different volatility measures?

I read the Euan Sinclair's book (Volatility trading) in which he suggests different volatility estimators (Close-to-close, Parkinson, Garman-Klass, ...). I am inquiring about what is the best stock ...
23
votes
4answers
9k views

What is the best way to “fix” a covariance matrix that is not positive semi-definite?

I have a sample covariance matrix of S&P 500 security returns where the smallest k-th eigenvalues are negative and quite small (reflecting noise and some high correlations in the matrix). I am ...
1
vote
0answers
75 views

Sampling and/or asymptotic distribution of a function

Assume we have the following function: $$f(p) = \frac{1}{(1-p)d}\ln\left(\frac{1}{T}\sum_{t=1}^{T}\left[\frac{1+X_t}{1+Y_t} \right]^{1-p} \right)$$ where $d$ is a constant $T$ is a constant $X_t$ ...
3
votes
1answer
105 views

Summary statistic for the average probability of default?

I have the following scenario: Let $X_i$ denote the event where some institution $i$ 'defaults' (don't worry about the exact definition of a default here, it is not relevant to the question at hand). ...
0
votes
2answers
168 views

Estimate weekly, yearly quantities from finite samples

I'd like to estimate from a daily prices serie $P_t$ with $N$ observations a quantity such as the variance of the weekly returns. I will use $\ln\left(\frac{P_{T+5}}{P_T}\right)$ assuming 5 days in a ...
5
votes
2answers
2k views

What are the econometric assumptions in the Fama-Macbeth procedure (1973)?

Fama-Macbeth (1973) introduce a two stage cross-sectional regression method (http://en.wikipedia.org/wiki/Fama%E2%80%93MacBeth_regression). 1) If I was to regress stock prices (or returns) on a ...
0
votes
1answer
237 views

Calculating the Sum of Squared Deviations between two Normalized Price Series

How can I calculate the sum of square deviations between two normalized price series according to (Gatev et. co 2006)? My normalized price series of stocks $X$ and $Y$ consist of the cumulative total ...
6
votes
2answers
234 views

Co-integration constraints of coint(X,Z) given coint(X,Y) and coint(Y,Z)?

The Augmented Dickey-Fuller Test can be used to measure how well ranked certain pairs are against others for co-integration. So then say we have a known co-integration between ...
3
votes
1answer
615 views

Normality assumption in Sharpe ratio

I have read that the Sharpe ratio imposes a normality assumption, but I fail to see how. Standard deviation is statistic for any type of distribution. Anyone have any ideas?
2
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0answers
155 views

Correlation between idiosyncratic residuals and forward returns

The classic mean-reversion strategy is to calculate an "expected return" (alpha) by computing the raw return for each security and then remove the part which you think is market driven. Statistically ...