Questions tagged [finance]

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

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t-day covariance matrix from daily return data

How do I get t-day covariance matrix from daily return data? I have an idea of how to calculate t-day variance from daily return data. From 14.6, 14.7 in Options, Futures and Other Derivatives by John ...
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Normality assumption of structural shocks in Vector Autoregression model

I’m currently working on forecasting yield curve evolution over time using a state space model where the transition dynamics are described using a vector autoregressive model of order 1. This model ...
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What is the distribution of the daily change rates of S&P 500?

I was wondering what is the distribution of the daily change rates of the S&P 500. It doesn't seem to be distributed normally (using qq plot for example).
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Comparing constants multiple regressions

My objective is to compare the returns of several portfolios. In short, I have multiple independent variables (4) that benchmark returns of different market portfolios (Carhart 4-factor), where the ...
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Estimate the mean vector and the covariance matrix using the simple returns

I would appreciate help with how to to estimate the mean vector and the covariance matrix using the simple returns in R. I have historical (weekly) values of five stocks from a capital market for a ...
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CAPM Estimation

Please that might sound basic for all of you but I am not an expert and I need to estimate the following model using OLS regression: R= a + β1 RM + β2(z)RM + ε (the model is called conditional CAPM, ...
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What model for volatility spillover effect in R? [closed]

I am doing research to study the volatility spill[over] effect. I have time-series data of Indonesian stock price (Jakarta composite index or JKSE), an exchange rate (IDR/USD), and oil price (BRENT). ...
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Features are Relevant for Regression but not necessarily for Classification - what to make of this?

I have used the R Boruta package to check for feature relevance in predicting log returns of financial time series, the targets being the log returns themselves (for regression) and the sign of log ...
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From OLS regression to Logistic Model

I'm currently working on my master's thesis in finance. Without going into to much detail, my goal is to regress certain predictors on first-day returns (SPAC IPO performance). However, after ...
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How to test if day of week impacts a stock's return

Say you have the daily % change in a stock's price going back a few years, looking something like this: ...
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Are financial asset prices (Pt) log-normally distributed or arithmetic returns (Pt/P0)?

In finance, the price of an asset is given by the following formula. $P_t=P_0* e^r$ r=returns Pt = Price at time "t". P0 = Actual Price. Likewise, it is assumed that the yields (r) will ...
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Asset prices are in theory log-normally distributed

In finance, the price of an asset is given by the following formula. $P_t=P_0* e^r$ r=returns Pt = Price at time "t". P0 = Actual Price. Likewise, it is assumed that the yields (r) will ...
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When are continuous-time models important?

In Econometrics, majority of the models are in discrete-time setting, whereas when you move on to quantitative finance, continuous-time models are most prevalent. I get the theory and idea behind ...
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Is return normal or log normal?

I read that return is normal and stock price is log normal. But I also read that return is log normal. So I am confused about which it is. In the 14th Chapter of Options, Futures, and other ...
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How to compare different models in their ability to forecast the value-at-risk with Diebold-Mariano test?

I made value-at-risk forecasts for different models for the 95, 97.5 and 99%. I also made a dummy which equals 1 if the true return was below the value-at-risk, 0 otherwise. How can I compare those ...
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Discrete wavelet transform - DWT (beginner)

I recently stumbled upon this article : [https://www.bportugal.pt/sites/default/files/anexos/papers/wp201612_0.pdf][1] In the paper they use DWT and I am having trouble understanding how to construct ...
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Which raw data to include for heterogenous autoregressive (HAR) model

I constructed the realized variance of bitcoin returns per day from 8-10-2015 to today. The realized variance is calculated by taking the cumulative squared intra-day returns. 5-minute high frequency ...
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Bootstrap residual resampling in R

Since I am quite new to this topic I have a question regarding bootstrap techniques in R. I should generate a 10,000 bootstrapped time series by drawing with replacement from the residuals. This ...
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How to decompose class dummy variable in panel model?

Maybe this is a question more of research design... I am interested to research on analysts forecast ability (Dependent Variable) among two classes of analysts (1) Investment bank analysts (2) Non-IB ...
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Error when forecasting volatility with GARCH model in R [closed]

I am trying to forecast volatility on four different time series which is returns of SP500, Nasdaq 100, Dow Jones and Russel 2000. the four time series consists of 3259 observation and is divided into ...
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How to decide which "outliers" to get rid of?

I have thinking about this problem for a while but couldn't quite formulate a proper solution myself. I am also not even sure if it is appropriate to speak of "outliers" or if the term "...
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egarch using rugarch package in R

Hello. I have been trying to wrap my head around GARCH (via rugarch package) for the past week and been trying to mimic the numbers as shown at vlab nyc's website. I have not confirmed where they get ...
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Why an agent can't learn on cheat data?

I want to train a FinRL model which will trade on an exchange using Ray Tune. I tried two different tune runs: with future data(you can find this code by "#Future data") and without. I ...
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Why is Binning, Weight of Evidence and Information Value so ubiquitous in the Credit Risk/Finance industry?

In the credit risk industry (and finance industry as a whole, at least here in the UK), there is a very common and accepted 'proper' way to build scorecards. The general framework seems to be: ...
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Can the cointegration coefficient be negative?

I am trying to understand the cointegration coefficient, $\gamma$. In the following case, $$P_{A,t }- \gamma P_{B,t}= \varepsilon_t$$ where $P_{A,t}$ and $P_{B,t}$ are the prices of the assets A and B ...
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My topic is ''determinant of demand on lease financing by SMEs''

Demand in finance is a three stag process, at stage one the SMEs will be asked whether they are applied or not. At stage two, those indicated applied will be asked whether their application approved ...
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Help in Understanding the Estimation Procedure Followed in a Paper

I would like to build a Markov regime-switching based early warning system. From the several papers I've skimmed through, [1][2][3][4] they go on about estimating a Markov regime-switching model as a ...
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Local Outlier Factor (LOF) in Financial Time Series

I'm using Local Outlier Factor (LOF) in financial data with 40 features. When I use the algorithm I can achieve scores outliers, but I can't understand how I can get my algo to tell me the connection ...
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2 votes
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Case-Shiller Index methodology [closed]

I'm new here, I may be in the wrong forum, not sure. With a little 'stretch', this can be described as a regression question. I am trying to find a definitive specification of the index construction ...
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What is the expected inverse stopping time for an Ornstein-Uhlenbeck process?

Let $X_t$ be an Ornstein-Uhlenbeck process defined by the following SDE: $$\text{d}X_t = \theta(\mu − X_t) \text{d}t + \sigma \text{d}B_t$$ where $\theta > 0$ and $\sigma > 0$ are parameters and ...
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time FE vs. individual FE vs. twoways FE

In my paper I want to know if there is correlation between sustainability and and the performance of a company. I want to explain the StockPrice with a lot of other variables and for sure the ESG-...
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Bivariate GARCH model to obtain dynamic optimal hedge ratio - R

The optimal hedge ratio is the ratio of the covariance between the futures and spot price, to the variance of the future price. I estimated it already as the slope coefficient of an OLS regression of ...
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GRS test (Gibbon, Ross and Shanken (1989) in Python

I'm writing a term paper, where we need to compare the Fama-French 5-factor model and a q-factor model. For the empirical part, I'm using the Python-based Linearmodels library by Kevin Sheppard. My ...
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Models/techniques for financial data quality

I'm part of a team tasked with assuring data quality of a large database of financial data (credit cards, collaterals, etc..). We're essentially looking for anomalies, such as single outliers or ...
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Can we use regular Loss Function in Finance Deep Learning? (Exploring the properties of different loss functions)

I am currently working on replicating financial deep learning papers to see if they actually would work in real markets. I have this question that bothers me. It is okay to use regular lossFunction ...
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Standard Deviation shows that a price series is riskier but annualized volatility computed with the log of returns shows the opposite

I apologize if this is not a smart question, but it seems contradictory that the standard deviations of two price series show that series A is riskier, but when I plot the annualized volatilities (...
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Optimal Mean Reversion Trading with Ornstein-Uhlenbeck Process

TL;DR: I'm getting a very different answer when trying to solve the problem described in this paper using a different approach (which seems simpler to me). I probably have some error in my reasoning ...
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Convolution of Binomial and Poisson Distributions?

I am currently working through the paper Estimation of Probability of Defaults (PD) for Low-Default Portfolios: An Actuarial Approach In Section 2 of this paper, the author provides the following ...
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2 votes
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Time series: how much past predicts future

In financial (time series) statistics and forecasting we usually assume that the past of a series can predict the future to some extent. Every financial ad will warn you that investors should not ...
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Make 21-days ahead forecast with daily log return data?

I want to make daily 1-days and 21-days ahead forecasts of a stock price. I have used daily log return data for both 1-day and 21-days forecasts. Now I'm not sure if that is correct for the 21-day ...
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Calculations to forecast repayments on loans

I'm working on a dataset which includes the salaries of recent graduates in various job sectors. The data consists of students that have graduated in 2020 throughout the UK. I have calculated tuition ...
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Beta less than 1 despite the market standard deviation is lower than the one of the stock

I have a really dumb question. As an exercise, I calculated the beta of a stock with respect to the market in which it is listed. However, I noticed that although the standard deviation (and ...
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Interpretation of Cointegration Test Results

I ran the Johansen Cointegration Test and "Phillips & Ouliaris" Cointegration Test on the past 7 years of data of Oil Futures (BZ=F), Gold Futures (GC=F), Gold ETF (GLD), and Silver (SLV)...
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Is survival analysis/time to event prediction with my data a futile endeavor?

I have a transaction history of loans. Each row represents a monthly update/payment made on a loan, where the columns are loan ID, features like current principal, house value, days since the loan was ...
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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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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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