Questions tagged [finance]

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

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17 views

Lognormal distribution question [closed]

Can someone help explain this. I have to do X1 + X2 with x1 and x2 having a covariance between 1.3. x1 is N(1,5) and X2 is (-2,2)
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Examine price changes vs price returns

In empirical financial analyses, is there a difference when examining stock price changes and stock price returns? Would a model with a response variable price changes tell a different story than ...
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Help interpreting event study methodology of a famous research article

I wonder if someone out there familiar with reading research articles, especially finance research can help me interpret which event study methodology the author uses in her famous research article. ...
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46 views

bootstrap p value

Using our baseline bootstrap, for each fund i, we draw a sample with replacement from the fund residuals that are saved in the first step above, creating a pseudo–time series of resampled residuals, {...
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RMSE increases in test data while correlation also increases

I use deep networks to predict stock future return, and find that in the training data, the RMSE decreases and the correlation between label and the predection increases, which is normal. However, ...
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An Intuitive Explanation of Multifractality in Financial Time Series

Can anyone please give an intuitive explanation of multifractality in financial time series? Most definitions I came across are either purely mathematical or not in relation to finance. As for the ...
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How to show Clayton copula is continuous and decreasing at $\theta=-1$?

Clayton copula is defined as \begin{align*}C_{\theta}(x,y) =& \text{ } (max(x^{-\theta}+y^{-\theta} - 1),0)^{-\frac{1}{\theta}} \text{ if } (x,y) \in (0,1]^2\\ =& \text{ }0 \text{ otherwise} \...
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Can I score Pincode on the basis of financial data?

I have a financial dataset on distinct Pincode level, one of the feature is pincode and other are delinquency, cheque bounce, delinquency amount etc. I am looking to build a model where I can score ...
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Correctly Interpreting Regression Coefficients For Financial Returns Data

I'm running some regressions on daily return data, and I want to make sure I'm interpreting the coefficients correctly. Right now X is a single column of values ...
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Modeling a Time-Series Variable as a Function of Another

I'm pursuing an academic research project aiming to look at the effects of news coverage on a company's stock price. In order to do so, I hope to index coverage of an event into a single time-series ...
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1answer
20 views

How to get daily returns from irregularly spaced price time-series?

I have a timeseries that has irregularly spaced time indices as below ...
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Different prediction performance when scaling data ALREADY between 0 and 1

I am fitting a LSTM neural network for time series forecasting on realized volatility data available here. I am only using one of the variables in the dataset, namely 'rv5' or the 5-minute realized ...
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1answer
43 views

Test whether expected shortfalls of two distributions are equal

I have paired samples of size 1000 from two distributions. I would like to test a null hypothesis that the 2.5% expected shortfalls1 of the two distributions are equal. How can I do that? (This is a ...
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45 views

Test whether expected shortfalls of two portfolios are equal

I have about 2000 daily observations of historical share prices for a handful of companies. I use a rolling window of 1000 observations to model their joint distribution. From each of the windows, I ...
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Correlation of Financial Returns using Period-End vs. Period-Average Values

I have two time series of financial returns for assets $A$ and $B$ defined below for $n$ periods. The return $a_i$ is the percent growth in the asset price of $A$ using period-end values for $i-1$ and ...
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1answer
57 views

linear regression on time series - has to be stationary, even when finding relationship between X and y?

Question I am finding a relationship between the stock price and other features(predictors) such as the popularity among users or the price of ingredients. My goal is not to predict the future stock ...
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Micro or Macro average for an unbalanced multilabel stock market data?

Will like to seek some veteran feedback on this. I am working on an unbalanced, multilabel stock market dataset for educational purposes. The dataset shape looks like this ...
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92 views

Using a VAR model to predict stock prices

I ran into an issue while trying to predict stock prices using a Vector Autoregression (VAR) model. After noticing that all the series are non-stationary (see example below): I took first differences ...
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15 views

How to calculate synchronized returns among two different stock market using DCC-GARCH?

I am working out with the thesis paper Cheang(2018) to calculate synchronised returns between two stocks from different markets. I am trying to code this in R. I am using rmgarch package and using <...
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29 views

Should I use overlapping sequences of training data from a financial time series?

I am new to neural networks, and I would like to use one for trend prediction in a financial time series $p_0,p_1,\dots$. More precisely, I am trying to predict a certain future trend measure $T(S_i)$ ...
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19 views

Cointegration with Multiple Structural Break in R

I am trying to find cointegrated stocks in S&P 500. I have data on all the 500 S&P stocks from 2000 to 2021 which includes multiple structural breaks. I am doing the analysis in R. Currently I ...
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24 views

Overlapping vs. non-overlapping financial returns in machine learning algorithms

Dear all I have a question with respect to overlapping observations when using any machine learning algorithm. When I want to test predictability say of weekly or monthly returns with some set of ...
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31 views

Presence of underestimation bias in earnings predictions

I am working on a financial data that entails forecasted revenue a company generates over a fiscal quarter and the actual revenue for that quarter. ...
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1answer
32 views

Linear regression of time series with heteroskedasticity

I am trying to find if the stock market movements on average and in extreme conditions do affect gold prices. I am following the regression model proposed by Baur and McDermott (2010) which is given ...
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How to decompose the variance of log book-to-market ratio into components using GMM in Vuolteenaho (1999)?

I'm reading Vuolteenaho(1999). In this article, the author investigates whether the variation in stock market valuation level is driven by expected future cash-flows or by expected returns. In part V....
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1answer
33 views

How to compute realized volatility

I am provided with a dataset consisting of an open book and a trade book The open book data has the following columns: Bid price/size 1 Bid price/size 2 Ask price/size 1 Ask price/size 2 time id ...
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In-sample forecast accuracy of Beta (Kalman filter)

One can calculate time-varying betas (known from the CAPM) using the Kalman filter. For example, one can calculate the in-sample forecast accuracy using the MAE. $MAE = \frac{1}{T}\sum_{t=1}^T|\hat{R}...
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What are the differences between different volatility models?

I would like to understand the differences between different volatility models like in simple terms and what are pros and cons over the other models Local volatility Model(Dupire) Heston Model SABR ...
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1answer
29 views

What are the conditions on standard GARCH coefficients

it is hard to find the full list of restrictions on GARCH(p,q) coefficients. Let me clarify. First, define GARCH(p,q) for a zero-mean returns time series as: \begin{equation} \label{eq:garch_pq} \...
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Jump diffusion -advantages

What would people say is the advantage of using a Merton jump-diffusion model, in terms of what it models and it's key characteristics/ features?
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1answer
57 views

Which standard errors do I use for the Fama-French three-factor model?

I am doing a linear regression with the Fama-French three-factor model with data from the stock market I built a portfolio out of. (I also use Betting Against Beta, Short Term, Long Term and Momentum ...
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Confidence Interval using % changes (Trying to classify whether variation from SMA is significant)

0 So I'm attempting to figure out when a drop in the price of a security is "statistically significant". The distribution of the difference is log-normal (makes sense because it can only be ...
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10 views

Appropriate statistical procedures to compare sales based on Internet search keys

This is my first question ever on Stats StackExchange and I am hoping to get some guidance from the community. I have graduated with a BSc in Statistics, so I am familiar with the fundamentals of ...
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42 views

Markowitz and inverse covariance matrix

Quite often in online literature it mentions that Markowitz CLA requires the inversion of the covariance matrix. In the python code samples I have seen displaying an efficient frontier and marking the ...
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2answers
124 views

How do I generate $n$ random variables that follow a correlation matrix with individually log normal distributions?

Short and sweet: I'd like to model $n$ random variables representing price changes of individual assets. Each of these should be distributed as a log normal variable with a median of 1. Is there a way ...
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11 views

What is the distribution of risk adjusted return of the population of 'x' stock portfolios, where stocks are selected from a universe of 'n' stocks

As part of a research project, I am trying to determine the distribution of the risk-adjusted return (mean return / standard deviation of return) of a 20 stock portfolio, created from a universe of ...
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1answer
34 views

I am a bit confuse about running a regression

I am a bit confuse about running a regression. Independent Variables are as: X1 = Profitability Index X2 = Operational Index X3 = Cost per employee X4 = Leverage Ratio I am confused that can I use ...
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34 views

Rolling forecast vs. static training data for financial timeseries?

I want to train a statistical model to predict financial asset returns. I'm wondering whether it would be more effective to train a rolling forecast model rather than training a single model with a ...
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11 views

Weak form of market efficiency and random walks

The weak form of market efficiency states that historical prices should not provide predictive information that is not already incorporated in the current price. Hence, predictions based on the past ...
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19 views

How to interpret regression results (simple returns, first difference)

I have run the following regression: where, r is the simple return of a daily stock index, SENT is the daily level of a custom sentiment index, and ΔVIX is the first difference of the VIX (the VIX is ...
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1answer
23 views

Data splitting for train and test set

I have a data from 2010 to 2020 (4000 observations) and I want to build a classification models (default/non default). What I see is that 33% of observations comes from 2020 and in this year the ...
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42 views

GRS test sharpe ratio and slope efficient frontier

I am investigating a multifactor asset pricing model and use time-series regressions on 25 portfolios sorted on size and BM. Therefore, I am implementing a GRS-test using the GRS.test package in R. ...
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1answer
63 views

Using R auto.arima and arima.sim for stock prices

I simulate around 16000 stock prices with using auto.arima and arima.sim and I have two questions. Do I need to use plain ...
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1answer
57 views

Testing if log returns are statistically significant from 0

I have created a algorithm that signals when to buy a certain stock. When that signals is generated a buy the stock and hold it for lets say 10 days. So the log returns for that period will be ln(p(t+...
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1answer
29 views

quantiles and cut by value range differences

Let's assume we have 6 companies with these returns: 10%, 8%, 7%, 7%, 1%, -5% If I want to cut them by terciles, the grouping will be: ...
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68 views

Event Study - Non Trading Days

I am currently conducting a event study for my research project on M&A. I have all data available and want to use https://www.eventstudytools.com/. But there is one clear which is not apparent to ...
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1answer
101 views

Should we square return to calculate ACF and PACF?

In sources such as this one, someone would square the data before calculating ACF and PACF. However, it is not universally done. So should we square the time series data before calculating ACF and ...
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1answer
37 views

What assumptions are required for structural breaks tests in time series?

Context I'm doing research related to structural change in stock price time series. In order to test whether some chosen event is a structural break or the series has a structural change, I conduct a ...
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1answer
42 views

Calculating $\mathbb{E}^2(\sigma_t^2)$ where $\sigma$ is a GARCH(1,1) process

Given that $\alpha=0,113079$, $\beta = 0,873884$, $\omega = 0,0000081$ (and that $\text{kurtosis} = 235$), I need to calculate a call price using GARCH volatility: https://www.researchgate.net/...
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How can i use an ARIMA model to explain the an effect of news regarding COVID-19 on a stock market index?

My thoughts were to model the time series of the stock index up until the particular day for the news I am looking at and forecast using my model. Then I would compare the forecasted result to the ...

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