From 1e8be5293c3c753a32598c7b621d88de200068bc Mon Sep 17 00:00:00 2001 From: jaketothepast Date: Thu, 14 Dec 2017 23:52:57 -0500 Subject: [PATCH] Adding tags to posts --- .../day-trading-generating-training-data.md | 25 +++++++++++++++++-- .../post/day-trading-simple-moving-average.md | 1 + .../quick-tips-javascript-password-verify.md | 1 + 3 files changed, 25 insertions(+), 2 deletions(-) diff --git a/content/post/day-trading-generating-training-data.md b/content/post/day-trading-generating-training-data.md index 5e48c00..a51e3d8 100644 --- a/content/post/day-trading-generating-training-data.md +++ b/content/post/day-trading-generating-training-data.md @@ -2,6 +2,7 @@ title: "Getting Into Day Trading: Analyzing The Moving Average" date: 2017-11-04T14:11:54-04:00 draft: true +tags: ["day trading", "data analysis", "julia"] --- Now that we have a Julia environment good to go, and a dataset available, time to start doing some real analysis. @@ -11,7 +12,27 @@ plotted in all of it's glory. Let's take a look at the closing costs (y) plotted ![Image](/img/post/WLTW_CLOSING_COSTS.png) -Not bad, we can see an ok trend going from January to December 2016. This data isn't very useful yet but it does -showcase some awesome Julia packages. +Not bad, we can see an ok trend going from January to December 2016. This data isn't very useful yet but I can +showcase some awesome Julia packages, and how I generated the graph. + +I used DataFrames.jl to store the data, Query.jl to grab a subset of the data, and Gadfly.jl to plot the data. +All of these are excellent libraries for doing your thing when analyzing. + +```julia +data = readtable("prices.csv", header=True) +q = @from i in data begin + @where i.symbol == "WLTW" + @select {i.date, i.close} + @collect DataFrame +end + +p = (q, y=:close, Geom.Point, Guide.Title("Closing Costs: WLTW - 2016")) +draw(PNG("wltw_closing_costs.png, 6inch, 4inch), p) +``` + +Now I'd like to add the plots for the 3-day SMA, and the 5-day SMA to the plot of WLTW closing costs. What these +are, are the average of either the last 3 days or the last 5 days for a single datapoint. I believe that +by doing so, we may be able to visualize if either datapoint is adequate in predicting trends in this data. I'll be looking for +how close any given moving average is to the actual trend of the close costs for the WLTW security. diff --git a/content/post/day-trading-simple-moving-average.md b/content/post/day-trading-simple-moving-average.md index 32e1ca4..1c33cbc 100644 --- a/content/post/day-trading-simple-moving-average.md +++ b/content/post/day-trading-simple-moving-average.md @@ -2,6 +2,7 @@ title: "Getting Into Day Trading: Simple Moving Average" date: 2017-10-28T18:13:45-04:00 draft: false +tags: ["day trading", "data analysis", "julia"] --- We've all heard the get rich quick schemes right? That someone somewhere has some plan to game the stock market to make diff --git a/content/post/quick-tips-javascript-password-verify.md b/content/post/quick-tips-javascript-password-verify.md index 26864ef..26fb7c5 100644 --- a/content/post/quick-tips-javascript-password-verify.md +++ b/content/post/quick-tips-javascript-password-verify.md @@ -2,6 +2,7 @@ title: "Quick Tips: Javascript Password Verification" date: 2017-10-28T10:30:49-04:00 draft: false +tags: ["javascript", "quick tips"] --- I just had to write client-side password verification for work at [Verodin](https://verodin.com),