We are a team of academics with both research and teaching backgrounds and we believe that education should be free and accessible for everyone who wishes to learn. Our goal is to deliver good quality educational content for every level, to explain complex concepts in the simplest manner possible, and to share our passion for learning.
ABOUT US Savva Shanaev Associate Fellow (Higher Education UK) Ph.D. in Finance, Northumbria University, Newcastle
Arina Shuraeva BSc in Economics, University of London
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That was helpful!! I'm in a data science course but it lacks statistic classes, so I can barely tell what that bunch of indicators on the summary mean. Do you recommend any book, course, paper or anything on statistics to help me understand the basis of it and what the indicators mean?
Sir, I've got a question. Excellent video! 🎉 I will take my time to research more about this method. I was just wondering if you have a source of the complete formula for Standard Deviation. I believe there is no software that makes the whole algorithm directly.
Great video, what about a video on 6 (or 4) Factor Model? Fama-French 5 Factor (or 3) + Momentum (excluded by Fama & French due to difficulties in explainability but evaluated by Carhart in the 4 Factor Model)?
Thank you for the video! Quick question: if I want to use German-Klass to estimate daily volatility (as an alternative of a sum of squared intraday returns), do I just omit the summation and 1/n division?
hey,thanks for your videos! And I want to ask some questions .I am now using R language to reproduce the prediction effect of the HAR-RV model. I first divided it into a test set and a training set, and then I used the training set to regress it to find its coefficient. Then I want to know, for RVt-1, RVt-5, RVt-22, what should I do if the training set does not meet the number of lagged items. For example, for RVt-22, should the regression data start from RV, RVt-1, RVt-5 corresponding to the first item of RVt-22?
Great Content! Video request: Factor decomposition of an example CTA hedge funds return, regressed against factor indexes like volatility, carry, mean reversion/value, time series momentum
Another great video. Really appreciate your content and efforts to make the calculations understandable. Also appreciate the context and qualitative considerations that are discussed after doing all the math. Thanks for all you do.
Hi, thank you for the clear explanation. Does anyone know how to run a monte carlo simulation by assuming that the stock return follows the t-distribution? By searching on the internet I found that in Excel the formula to generate the random numbers is: =mean + stdev * T.INV(RAND(),df) where the mean, stdev, and df are determined from historical data. However, from your example, you mentioned that the standard deviation need to be scaled by sqrt((df-2)/df). Do I also need to scale it here to generate the random numbers? It'd be nice if you can point me to relevant books/articles on this topic. Thank you.
why did u multiply insensitive assetes and liabilities with duration generated via whole asset and liabilities ? isnt that true that only sensitive assets may change if IR changes.
Thank you for your kind words regarding the research paper. I would be happy to clarify the software utilized for data analysis. The analyses and graphical representations were conducted using Excel?
Thank you for the great video, i have a question as well. When they say that the estimation window and the event window needs to not overlap, did we just achieve this by not taking the same date as the date that the anticipation window starts? or we need to leave more days in bettween?
