Richard Herron
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 Nov30 comment zero-sum active management riddle (As well, I would guess that the Roll critique of these pricing models is particularly strong in these less-sophisticated markets.) Nov30 comment zero-sum active management riddle @QuantGuy -- Other than the case of value-weighted portfolios and value-weighted market factor (i.e., CAPM), I don't know of a requirement for $\sum_i w_i \alpha_i = 0$ and $\sum_i w_i \beta_i = 1$, where $w_i$ is the value weighting for each portfolio $i$. Nov29 comment How to generate a random price series with a specified range and correlation with an actual price? How? Try AAPL and MSFT. There are about 5000 more. Nov28 answered How to generate a random price series with a specified range and correlation with an actual price? Nov28 answered zero-sum active management riddle Nov27 reviewed Approve How to use Itô's formula to deduce that a stochastic process is a martingale? Nov18 comment Convexity of BS Equation for Call and Put My first stop is checking $Call(\cdot, \lambda \sigma^2_1 + (1 - \lambda) \sigma^2_2) \leq \lambda Call(\cdot, \sigma^2_1) + (1 - \lambda)Call(\cdot, \sigma^2_2)$. Nov14 comment How to check if a timeseries is stationary? @Dail -- There are a variety of tests, but Wald tests that all coefficients are jointly zero is probably the easiest. I searched for how to do this in R, but wasn't too successful. You will likely have to grab a text book and code the tests yourself. (I switched to Stata for most analyses because hypothesis testing is so much easier). Nov14 comment How to check if a timeseries is stationary? @SKRX -- Yes, thanks. I should have included more commentary. He asked how to fit a GARCH model in R, so I gave some code. Once he determines the best-fitting GARCH model with ll, ic, and ssr, he can perform joint tests on the GARCH model coefficients. Nov14 comment How GARCH/ARCH models are useful to check the volatility? The plots are helpful, but to determine if the GARCH model fits, you should use statistics. Look at the log-likelihood, sum-of-squared-residuals, and information criteria across various specifications to see which fits best. Then perform joint test of the GARCH coefficients. If you fail to reject that all coefficients are jointly zero, then you don't need a GARCH model. Nov14 comment How GARCH/ARCH models are useful to check the volatility? fitted.values has +/- sigt (why isn't clear to me). You want to plot the positive sigt versus some time index. Something like this: y <- arch_model\$fitted.values[, 1] then x <- seq(1, length(y)) then plot(x, y). Nov14 answered How to check if a timeseries is stationary? Nov14 comment How to check if a timeseries is stationary? @Dam -- I will post some code in an answer. Nov13 comment Any recommendations for textbooks for an undergraduate course in mathematical finance? Are MFE/MSCF students not well-prepared? I would guess that you'll find the right level in Shreve's two book series. If these kids are really that tough, then use Duffie's. Although if these kids don't have exposure to the concepts in finance, then you may be best of with Hull's book and beefing up the math where necessary. Nov13 comment How to check if a timeseries is stationary? @Dam -- You can reject the unit root and still have time-varying volatility. Maybe you want to fit an ARCH model? Nov13 comment How to check if a timeseries is stationary? I agree with the Phillips-Perron test. The Augmented Dickey-Fuller test is not robust to the selection of the number of lags. The KPSS test differs from these two tests in its null hypothesis, which is trend stationarity. Sep22 awarded Enlightened Sep22 awarded Nice Answer Sep6 awarded Nice Question Sep2 comment Garch modelling on Stata @sheegaon -- Good point. But it's a RTFM answer (or a LMGTFY answer) that doesn't add much to either community. I will see if the QF community closes.