1/23/2024 0 Comments Maximal drawdown![]() # We are going to use a trailing 252 trading day window The following should do the trick: import pandas as pd Lets say we wanted the moving 1-year (252 trading day) maximum drawdown experienced by a particular symbol. You can get this using a pandas rolling_max to find the past maximum in a window to calculate the current day's drawdown, then use a rolling_min to determine the maximum drawdown that has been experienced. This is a short example of the dataframe used: CLOSE_SPX Close_iBoxx A_Returns B_Returns A_Vola B_Vola Does anone know how to implement that in python? considering the minimum only from a given maximum onwards on the timeline. ( df.CLOSE_SPX.max() - df.CLOSE_SPX.min() ) / df.CLOSE_SPX.max()Ĭan't work since these functions use all data and not e.g. I need to calculate the a time dynamic Maximum Drawdown in Python. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.įor technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tai Tone Lim (email available below). If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. You can help adding them by using this form. ![]() We have no bibliographic references for this item. It also allows you to accept potential citations to this item that we are uncertain about. This allows to link your profile to this item. If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. See general information about how to correct material in RePEc.įor technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact. When requesting a correction, please mention this item's handle: RePEc:wsi:wschap:9789812562586_0013. You can help correct errors and omissions. ![]() " Sustainable Investing and the Cross-Section of Maximum Drawdown,"Īll material on this site has been provided by the respective publishers and authors. " On Solving Robust Log-Optimal Portfolio: A Supporting Hyperplane Approximation Approach," " Portfolio optimization with behavioural preferences and investor memory,"Įuropean Journal of Operational Research, Elsevier, vol. " Hedge Fund Portfolio Diversification Strategies Across the GFC,"Ģ014-32, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.ġ4/27, University of Canterbury, Department of Economics and Finance. Allen & Michael McAleer & Shelton Peiris & Abhay K.
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