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21 views

Optimized Method to Calc Real Rates of Return From Monthly Nominal Rates

I wrote the following VBA code to calculate real rates of return using Robert Shiller's dataset: Note: This calculation is for forecasted returns so I have no prices available to do the calculation by ...
0 votes
0 answers
28 views

Calculation of daily dividends from total return index data

I have a question regarding the inclusion of dividend payments in total return indices, but I have no background in finance, so I'm hoping someone here can help me out - any help is highly appreciated!...
0 votes
2 answers
10k views

How to calculate the log return of portfolio?

Suppose that we have five trades each day with these returns ($R_{day,trade}$) and we have 300 days in total: $R_{1,1}$, $R_{1,2}$, $R_{1,3}$, $R_{1,4}$, $R_{1,5}$ $R_{2,1}$, $R_{2,2}$, $R_{2,3}$, $R_{...
3 votes
2 answers
3k views

How to annualize the correlation matrix?

If asset returns are daily, and the asset return covariance matrix, $\Sigma$, is annualized by $\Sigma \times 252$, do I also multiply the correlation matrix by 252 to annualize it?
0 votes
0 answers
46 views

Cumulative returns when shorting with regards to variance drag

What is the convention when calculating/analyzing daily returns for a strategy when shorting is involved? I found the following answer regarding variance drag useful in understanding why there is a ...
0 votes
1 answer
129 views

Performance attribution of indices to their sector weights

Is it possible to attribute performance of indices (monthly returns and risk measures - Sharpe ratio, etc.) to their sector weights (if I know them)? Example: I know the monthly performance of ...
3 votes
2 answers
105 views

Expense ratio over time

I'm trying to reproduce the results in the table below from this article of Investopedia, but none of my calculations match. What is the correct way to calculate the expense ratio in this case?
-1 votes
1 answer
57 views

Am I able to find individual returns from total weighted average of returns? [closed]

As titled states… I am trying to figure out how to solve for individual return given average weighted total return and weights of individual returns? For example: 2% = (r1 x 0.2) + (r2 x 0.5) + (r3 x ...
2 votes
3 answers
2k views

Daily to Monthly Performance Attribution - Getting Effects to equal the Excess Return

I am building a performance attribution tool on Python to help us understand the asset allocation, stock selection effects of our fund. We are using daily price data for each component within the ...
24 votes
2 answers
21k views

Discrete returns versus log returns of assets

There have been similar posts here already but nevertheless I find the question worth posting: why do some people claim that log returns of assets are more suitable for statistics than discrete ...
4 votes
4 answers
1k views

Central limit theorem and normality assumption of asset return distribution

Can central theorem justify normality assumption of assets return distribution? And if it can why the empirical evidence show this assumption, which many finance models are based on, is a far cry from ...
0 votes
1 answer
166 views

What are the most common methods to model fat tails in the changes of asset prices?

I was wondering what the most common, or most popular, ways - in both academia, and industry - there were to model the fat tails of volatility in asset prices changes. I am presuming a basic Brownian ...
-2 votes
1 answer
420 views

How to calculate return on a series of long position for each price point

The return between two price points can be calculated as Price(present)/Price(previous) -1 Or, it can be expressed as ...
0 votes
0 answers
73 views

Does the interval of a portfolio's returns affect Sharpe and Sortino? If so, what's the gold-standard interval?

I'm currently creating a backtesting script and I've got to the point of calculating risk metrics. It seems like the interval (daily, weekly, or monthly) I use for returns heavily changes the ...
2 votes
1 answer
366 views

Fat tailed can be estimated through a t-distributions?

I have a simple question that makes me doubt a bit. In a multiple choise exam I ecountered this question: "if the stocks returns are not normally distributed, the fat tail effect can be estimated ...
1 vote
1 answer
76 views

Measuring extra return investors demand for a stock which cannot be sold?

How to roughly measure how much premium investors would demand if a stock could not be sold and its investors had to stick with it permanently using just dividends not capital gain as return? I am not ...
3 votes
2 answers
439 views

Why in Fama-French factor model relative market capitalization and book-to-market aren't used directly for predicting return rate?

Fama and French use the following formula for predicting stock returns \begin{align*} r=r_{riskfree} + \beta_1(r_{market}-r_{riskfree})+\beta_2(SMB)+\beta_3(HML) \end{align*} which basically means ...
0 votes
0 answers
51 views

Real domestic return

I would like to calculate the real domestic return of a foreign asset What I know Real price is $$P_{Real, t} = \frac{P_{Nominal, t}}{CPI_t}$$ where CPI is consumer price index. And I know that the ...
1 vote
3 answers
943 views

Why can we assume that asset return rates are normally (or lognormally) distributed?

In many theories of financial mathematics it is assumed that asset return rates are normally distributed (e.g. VaR models) or lognormally distributed (e.g. Black-Scholes model). In practice, asset ...
1 vote
0 answers
260 views

Calculating returns from transactions

I have a collection of client transactions representing the trades of a single portfolio across multiple securities. What I'd like to do is the calculate the accurate ROI of each security and of the ...
0 votes
1 answer
398 views

Calculate weight of an asset

Suppose there are three assets, and the first asset has volatility 18%, the second asset has volatility 16%, and the third asset has volatility 16%. Suppose also that the first two assets' returns ...
-3 votes
1 answer
106 views

Should stock return series be modeled with a parametric distribution, or an autoregressive function? [closed]

If I have prior knowledg that a stock return series follows a parametric distribution, such as a Student t-distribution with 4 degrees of freedom, without actively looking for prior knowledge of ...
0 votes
1 answer
141 views

How do you simulate returns for a portfolio when you have Lumpsum + Monthly investments (SIP) in place?

I'm trying to simulate portfolio returns using Norm.inv function in excel. Inputs to the formula: Prob= Rand, Std dev= Historical, Mean= 5 year historical average. Its easy to do this when you're ...
0 votes
0 answers
533 views

What should degrees of freedom $\nu$ be set to when modeling financial returns that follow the t-distribution?

The closer the t-distribution degrees of freedom ($\nu$) is to 0, the more heavy are the tails, whereas high degrees of freedom recovers the normal distribution. In finance, what value is usually used ...
3 votes
0 answers
274 views

Marginal Distribution using GARCH model: How to do inverse probability transform?

I have $n$ return series. I fitted AR(1)-GARCH(1,1) to each return series. Then used probability integral transform, PIT(residuals), to transform the residuals to have a uniform distribution. Then I ...
1 vote
1 answer
116 views

Clustering the observations in a price or returns series [closed]

Given one stock, what value would there be in clustering the individual sample observations within that stock's historical prices series, or its return series? is univariate clustering done in finance?...
0 votes
0 answers
76 views

Does the $t$-copula or Clayton copula capture the dependence structure of empirical returns better?

Which copula captures the dependence structure of empirical asset returns better? the $t$-copula, which has symmetric tail dependence, or the Clayton copula, which has asymmetric tail dependence, and ...
1 vote
0 answers
777 views

Source on multivariate correlated geometric Brownian motion returns, not prices

Can anyone provide a source that formulates how to generate multivariate geometric Brownian motion returns using the Cholesky method with target correlation matrix, instead of correlated GBM prices? ...
0 votes
0 answers
35 views

Are the correlations of multivariate stock prices preserved when converted to multivariate returns?

If data for multiple stock prices has a specific correlation matrix, is the correlation matrix preserved when those prices are converted to multivariate log-differenced returns?
3 votes
1 answer
356 views

Why does the likelihood of corner solutions in portfolios increase as the number of assets grows?

A three- asset portfolio doesn't seem prone to generating corner solutions, which are very high allocations to one of the assets and $0$ to the others. Instead, when the number of assets is low, these ...
4 votes
3 answers
525 views

Asset Allocation with near zero rates

With central banks pegging interest rates to near zero rates, an argument could be made that the future distribution of interest rates and bond returns are not normally distributed. How has modern ...
1 vote
1 answer
528 views

Do EWMA weights remove autocorrelation in asset returns?

I know that the exponentially weighted moving average (EWMA) volatility estimator drapes a decaying weight function over historical returns in order to weight the past according to the decay of their ...
3 votes
2 answers
280 views

Interpretation of a uniform asset return distribution

Typically asset return distributions are bell-shaped with most mass occurring in and around the center, 0% returns, and less so in the tails, with the left tail representing the probability of large ...
1 vote
1 answer
151 views

How to simulate asset prices/returns that display market regimes?

Are there any techniques that can make a multivariate random number generating process for stock prices/returns, like geometric Brownian motion via Cholesky, also include the simulation of a finite ...
1 vote
1 answer
80 views

How to adjust a portfolio's rate of return for contributions and withdrawals?

Suppose we have a portfolio with many assets. Since this portfolio receives monthly contributions and withdrawals, what is the best method to evaluate its global rate of return and avoid computing ...
0 votes
0 answers
66 views

Using Timeseries DB for Tracking Asset Performance over time

I am building a system that allows users to purchase digital assets, and i would like to know the asset's performance of individual users. A user may purchase an asset multiple time in a single day, ...
1 vote
1 answer
937 views

How to compute returns from cumulative returns in Python? [closed]

If X is a $T\times N$ pandas DataFrame of multivariate asset returns, the cumulative returns can be computed in python as (1 + X).cumprod() - 1 How can I reverse this operation so that I go ...
0 votes
1 answer
232 views

Which financial time series have a PDF and/or CDF?

Consider the following types of financial time series for a single publicly-listed stock: Price data Log returns Cumulative returns Each is computed from the item listed before it: log returns are ...
1 vote
1 answer
50 views

How to evaluate prediction(s) made of the asset return mean?

In finance, it is well-known that the expected value of asset returns, $\mu$, otherwise known as the average return or mean or first statistical moment, is difficult to predict. I think it was ...
3 votes
2 answers
1k views

Normality or Log-Normality of Regular Returns

Another old question on this site (How to simulate stock prices with a Geometric Brownian Motion?) inspired me to ask the following question: if we assume that regular returns could be normally ...
0 votes
1 answer
142 views

Does standardizing/normalizing asset returns change their skewness and kurtosis?

Asset returns are obtained by log-differencing prices. Standardizing or normalizing/scaling asset returns can be carried out by de-meaning the returns and dividing them by their standard deviation, ...
1 vote
3 answers
548 views

Any portfolio theories not based on asset returns?

For data, the mean-variance model for portfolio optimization uses asset returns to minimize portfolio risk (covariance matrix), which is asset returns volatility, and sometimes simultaneously ...
1 vote
1 answer
280 views

The ratio of upside deviation to downside deviation in portfolio weighting

I've been calling this ratio "acceleration" in my head, so I'll do the same in this post. The question is, is this relationship used anywhere and if so, how? My thought process is as follows. Risk ...
1 vote
0 answers
63 views

Time and asset weighted rate of return of a portfolio

If I have a portfolio with 3 initial assets on day 1 (say, stock 1 with beginning market value of \$100, stock 2 \$150 and stock 3 \$175) and after 10 days the stock 2 is sold for \$200, how can I ...
0 votes
0 answers
146 views

Replication of the paper: "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction"

I recently replicated the paper "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction" and found out that my estimation of the equity premium differs from the data provided ...
1 vote
0 answers
58 views

How to compute return series for a German government bond with a 0% coupon?

Recently, the German government issued a long-dated bond with a 0% coupon. I'm trying to implement a historical VaR model and would like to know the best way to model the historical returns of this ...
3 votes
2 answers
634 views

Distribution of simple returns vs logreturns

I understand that stock prices are conditionally modeled using a log normal distribution by the relationship $ y_t/y_{t−1}∼logN(μ_{daily},σ^2_{daily})$ $y_t∼logN(log(y_{t-1})+μ_{daily},σ^2_{daily}))$ ...
1 vote
1 answer
153 views

Portfolio & Asset Returns across Multiple Periods

The stocks of CK Tan's, Robertson's, and Tamashimaya are held by the hedge fund SSK. They hold an equally weighted portfolio. The end-of month prices of the stock during five months this year is given ...
1 vote
0 answers
48 views

Calculating the fundamental value of house price to separate bubble component from the price

The bubble in asset price is defined as the deviation of the asset value from its fundamentals, empirically Mendoza and Terrones (2008) measure the bubble as the deviation of an asset price from the ...
1 vote
1 answer
165 views

Jensen’s Inequality for returns on short positions

this is puzzling me. Say you have an asset A, that on day t+1 returns 1%, and then on day t+2 returns 1% again. If you invest $1 in A on day t (take a long position), then on day t+2 you have earned:...