Questions tagged [finance]

The science that describes the management, creation and study of money, banking, credit, investments, assets and liabilities.

Filter by
Sorted by
Tagged with
46
votes
4answers
44k views

What is the difference between GARCH and ARMA?

I am confused. I don't understand the difference a ARMA and a GARCH process.. to me there are the same no ? Here is the (G)ARCH(p, q) process $$\sigma_t^2 = \underbrace{ \underbrace{ \...
17
votes
5answers
8k views

Robust t-test for mean

I am trying to test the null $E[X] = 0$, against the local alternative $E[X] > 0$, for a random variable $X$, subject to mild to medium skew and kurtosis of the random variable. Following ...
15
votes
7answers
16k views

What machine learning algorithm can be used to predict the stock market?

Alternatively, to predict foreign exchange markets. I know this can get pretty complicated, so as an introduction, I'm looking for a simple prediction algorithm that has some accuracy. (It's for a M....
14
votes
4answers
15k views

Does applying ARMA-GARCH require stationarity?

I am going to use the ARMA-GARCH model for financial time series and was wondering whether the series should be stationary before applying the said model. I know to apply ARMA model the series should ...
11
votes
4answers
521 views

Is it a valid claim, that by differencing a time series, it loses its memory, and as a result its predictive power?

Marcos Lopez de Prado seems to be a well known and renowned machine learning expert in the field of finance. I am very far from his level, as have not yet finished my PhD in economics, and only have ...
11
votes
1answer
14k views

Variance of annual return based on variance of monthly return

I'm trying to understand the whole variance/std error thing of a time series of financial returns, and I think I'm stuck. I have a series of monthly stock return data (let's call it $X$), which has ...
8
votes
2answers
17k views

Is it a problem to get a negative adjusted r-squared?

Background: I have the cross-sectional model: $Y_{i} = a + b X_{1,i} + c X_{2,i} + d X_{3,i} + e X_{4,i} + \nu_i$. The application is corporate finance. So each $Y_i$ is something like the change ...
8
votes
9answers
4k views

Resources for learning about the Statistical Analysis of Financial Data

I realize that the statistical analysis of financial data is a huge topic, but that is exactly why it is necessary for me to ask my question as I try to break into the world of financial analysis. As ...
24
votes
1answer
30k views

Why stock prices are lognormal but stock returns are normal

Except for the fact that returns can be negative while prices must be positive, is there any other reason behind modelling stock prices as a log normal distribution but modelling stock returns as a ...
12
votes
1answer
7k views

First steps learning to predict financial timeseries using machine learning

I am trying to get a grasp on how to use machine learning to predict financial timeseries 1 or more steps into the future. I have a financial timeseries with some descriptive data and I would like to ...
9
votes
2answers
10k views

Difference between Time delayed neural networks and Recurrent neural networks

I would like to use a Neural Network to predict financial time series. I come from an IT background and have some knowledge of Neural Networks and I have been reading about these: TDNN RNN I have ...
11
votes
3answers
2k views

Good books/papers on credit scoring

I'm looking for recomendations of books on credit scoring. I'm interested in all aspects of this problem, but mostly in: 1) Good features. How to build them? Which have been proved to be good? 2) ...
10
votes
9answers
4k views

Tools for modeling financial time series

What modern tools (Windows-based) do you suggest for modeling financial time series?
9
votes
7answers
23k views

Correlation between two variables of unequal size

In a problem I am working on, I have two random variables, X and Y. I need to figure out how closely correlated the two of them are, but they are of different dimensions. The rank of the row space of ...
10
votes
2answers
690 views

Gigantic kurtosis?

I am doing some descriptive statistics of daily returns on stock indexes. I.e. if $P_1$ and $P_2$ are the levels of the index on day 1 and day 2, respectively, then $log_e (\frac{P_2}{P_1})$ is the ...
3
votes
1answer
3k views

Have MLE estimators for Generalized Pareto Distribution. Given a known value of $c$, how do I calculate $a$ and $b$ using the provided estimators?

I am doing research into the three parameter Generalized Pareto Distribution $$ f(x|a,b,c) = \frac 1 b\left(1+a\left(\frac{x-c}{b}\right)\right)^{\big(-1-\frac 1 a\big)} $$ for finding VaR and CVaR. ...
3
votes
1answer
508 views

Comparing 2 independent non-central t statistics

One estimate of the 'quality' of a portfolio of stocks is the Sharpe ratio, which is defined as the mean of the returns divided by the standard deviation of the returns (modulo adjustments for risk ...
2
votes
2answers
95 views

Why does the maximum probability of profiting occur when std. deviations of two different stock prices are equal?

I am working through the "Math for Quantitative Finance" course on brilliant.org. The following question was given as an example: An investor wishes to invest $700. There are two independent ...
7
votes
3answers
2k views

How to determine if there is a drop in revenue after a change in the system?

We recently released a new redesigned e-commerce website for a client. They are claiming to be seeing a 40% drop in revenue due to the changes. We have daily sales data going back a few years. We ...
5
votes
2answers
6k views

Finding correlations between financial time series

I have a task which is related to finding correlations between time series. I have two financial time series given, which contain daily interest rate offers of two financial contributors and I want to ...
4
votes
2answers
124 views

Need handy formula for $Var[\max(V, K)]$

In Appendix 12A, p. 262 of this book, the author Hull derives a handy, tractable formula for the expression $E[\max(V-K, 0)]$, where $V$ is a lognormally distributed random variable and $K$ is a ...
4
votes
1answer
2k views

Dynamic Conditional Correlation (DCC) model yields unexpected sign of fitted correlations

I'm calculating DCC between S&P500 and US 10-year bond index in R. However the results are in the unexpected sign. For example, as published by many, DCC between S&P500 and 10-year bond index ...
2
votes
1answer
119 views

Parameters in Autoregressive representation of an ARCH model

Suppose we have a $0$ mean time serie representing stock index returns about a title, $r$. I also know it follows an $ARCH(p)$ model with parameters $\omega$ and $\alpha$, specified in the following ...
2
votes
1answer
255 views

Detecting outlier cash movements

If I'm watching a series of accounts for transactions going in and transactions going out, I want to notice unusually large or transactions for any particular account on any particular day. So if ...
2
votes
1answer
378 views

Given this time series, what statistical methods would be used for description and forecasting?

These static cumulative default rate tables and charts come from this public report published by a credit rating agency. Basically, you take all the loans originated in a period of time (a "vintage")...
2
votes
1answer
168 views

Calculating portfolio volatility from portfolio returns vs. from covariance matrix

I'm having trouble understanding the difference in calculating portfolio volatility via the portfolio returns vs. via the covariance matrix. To be more specific: I understand that on the individual ...
1
vote
1answer
5k views

Forecasting with ARIMA and GARCH: does my plan look alright?

I have a time series containing the daily close price for a stock and I would like to perform a 10 days forecast of the volatility. I'm trying to follow this tutorial: https://talksonmarkets.files....
11
votes
1answer
2k views

Why Use the Cornish-Fisher Expansion Instead of Sample Quantile?

The Cornish-Fisher Expansion provides a way to estimate the quantiles of a distribution based on moments. (In this sense, I see it as a complement to the Edgeworth Expansion, which gives an estimate ...
5
votes
1answer
2k views

How to model time-varying correlation

Suppose I have two time-series variables, $\{x_t\}$ and $\{y_t\}$, where $t\in[1,T]$. I would like to model the correlation $\rho(x_t,y_s)$ as some function of $t$,$s$, and the difference $t-s$. In ...
2
votes
1answer
2k views

ARCH + GARCH sum to more than 1. Dropping the intercept

I am capturing the daily percentage returns of a stock index with dummy variables. I do this both including and excluding the intercept. I get quite different results. If I keep the intercept (image ...
0
votes
1answer
416 views

Comparison of returns of two investment strategies. Can some kind of randomization help?

My task is to compare the returns of two investment strategies using historical quarterly returns calculated from S&P 500 Index data. Example: If I chose 10 year horizon of an investment, then ...