Add bollinger bands (#16)

* Plot Bollinger bands * Add mode for Bollinger bands * Add mode for Bollinger bands * Fix Bollinger plot * Add test for price std * Remove extra lines + update docs * Fix typo
vnegi10 · Jun 25, 2022 · cd7cc20 · cd7cc20
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diff --git a/docs/src/index.md b/docs/src/index.md
@@ -43,6 +43,20 @@ The plots are interactive, which means you can hover your cursor over the data p
 
 - Plot title also contains $R^2$, which is a statistical measure representing the proportion of variation in the dependent variable that is explained by different features (independent variables) in this model. A value closer to 1 (maximum) indicates a good fit. The linear regression channel metric will therefore not be very useful when $R^2 < 0.50$.
 
+### Bollinger bands
+- These are price envelopes plotted at two standard deviations (std) above (upper band) and below
+(lower band) a simple moving average of the daily price. Since the distance towards the bands is
+based on std, it adjusts in response to the price volatility.
+
+- When the bands move closer (tighten during low volatility), it raises the chances of a sharp
+price movement in either direction. On the contrary, diverging bands indicate high volatility, 
+which might also indicate the end for any existing trend.
+
+- Prices often bounce between the two bands, which could be used to identify potential price 
+targets. For example, when a price bounces off of the lower band, and crosses the moving average,
+the upper band might be considered as the next profit target. Prices can also cross the bands 
+during strong trends.
+
 ### Fundamental Cryptocurrency Asset Score (FCAS) data
 - This metric tells us about the market health of an asset. In the case of cryptocurrencies, they are user activity, developer behavior, and market maturity, which are provided by [Flipside Crypto](https://app.flipsidecrypto.com/tracker/all-coins).
 
@@ -65,10 +79,4 @@ The plots are interactive, which means you can hover your cursor over the data p
 ## Run app
 ```@docs
 run_app(port::Int64, key::String)
-```
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+```
diff --git a/src/ConfigureApp.jl b/src/ConfigureApp.jl
@@ -7,10 +7,18 @@ currencies_list = ["BTC", "LTC", "BCH", "ETH", "KNC", "LINK", "ETC", "BNB", "ADA
 currencies = sort(currencies_list)
 currencies_index = 1:length(currencies)
 
-modes = ["Average price + Daily trade (AV)", "Candlestick + Volume (AV)", 
-         "Cumulative + Daily return (AV)", "Daily volatility (AV)", "MACD + Signal (AV)", 
-         "Linear regression channel (AV)", "FCAS data (AV)", "Developer + Community data (CG)",
-          "Exchange volume data per currency (CG)", "Overall exchange volume data (CG)"]
+modes = ["Average price + Daily trade (AV)", 
+         "Candlestick + Volume (AV)", 
+         "Cumulative + Daily return (AV)", 
+         "Daily volatility (AV)", 
+         "MACD + Signal (AV)", 
+         "Linear regression channel (AV)",
+         "Bollinger bands (AV)", 
+         "FCAS data (AV)", 
+         "Developer + Community data (CG)",
+         "Exchange volume data per currency (CG)", 
+         "Overall exchange volume data (CG)"]
+
 modes_index = 1:length(modes)
 
 durations = [7, 14, 30, 90, 180, 270, 365, 500, 750, 1000]
@@ -282,6 +290,19 @@ function run_app(port::Int64, key::String)
             return [P1]
 
         elseif mode_ID == 7
+            t1, t2, t3, t4 = plot_price_bollinger_bands(pair_ID, duration_ID, window_ID)
+
+            layout1 = Layout(;title="Bollinger bands for $(currencies[pair_ID])",
+                xaxis = attr(title="Time", showgrid=true, zeroline=true),
+                yaxis = attr(title="Price [euros]", showgrid=true, zeroline=true),
+                height = 500,
+                width = 1000,                           
+            ) 
+
+            P1 = Plot([t1, t2, t3, t4], layout1) # plots Bollinger bands   
+            return [P1]
+
+        elseif mode_ID == 8
             t1, fr = plot_fcas_data(pair_ID)
 
             layout1 = Layout(;title="FCAS metrics data for $(currencies[pair_ID]), overall rating = $(fr)",
@@ -295,7 +316,7 @@ function run_app(port::Int64, key::String)
             return [P1]
 
         # From CoinGecko
-        elseif mode_ID == 8
+        elseif mode_ID == 9
             t1, t2 = plot_dev_comm_data(pair_ID)
 
             layout1 = Layout(;title="Developer metrics for $(currencies[pair_ID])",
@@ -317,7 +338,7 @@ function run_app(port::Int64, key::String)
             P2 = Plot(t2, layout2) # plots community data
             return [P1 P2]
 
-        elseif mode_ID == 9
+        elseif mode_ID == 10
 
             t1, t2 = plot_exchange_vol_data(pair_ID)            
 
@@ -340,7 +361,7 @@ function run_app(port::Int64, key::String)
             P2 = Plot(t2, layout2)      # plots USD volume data for a given currency
             return [P1 P2]
 
-        elseif mode_ID == 10
+        elseif mode_ID == 11
 
             t_all = plot_overall_vol_data(duration_ID)
 

diff --git a/src/CryptoDashApp.jl b/src/CryptoDashApp.jl
@@ -11,4 +11,4 @@ include("GetDataFunctions.jl")
 include("PlotFunctions.jl")
 include("ConfigureApp.jl")
 
-end # module
+end # module
diff --git a/src/CryptoFunctions.jl b/src/CryptoFunctions.jl
@@ -74,6 +74,22 @@ function moving_averages(Price_df::DataFrame, duration::Int64, window::Int64)
     return Price_SMA, Price_WMA, Price_EMA
 end
 
+function moving_std(Price_df::DataFrame, duration::Int64, window::Int64)
+
+    # Price_df should have date order - oldest to latest
+    Price_col = Price_df[end-duration+1-window+1:end,2]
+    rows1 = length(Price_col)
+
+    Price_std = Float64[]
+
+    for i = 1:rows1-(window-1)
+        # Standard deviation over the period SMA is also being calculated
+        push!(Price_std, std(Price_col[i:i+(window-1)]))
+    end
+
+    return Price_std
+end
+
 function calculate_ema(Price_col::Vector{Float64}, window::Int64)
 
     k(window) = 2/(window+1)
@@ -117,5 +133,4 @@ function calculate_macd(Price_df::DataFrame, window_long::Int64 = 26,
                       MACD = MACD_col[window_signal:end], Signal = Signal_col)	
 
 	return df_ema
-end	
-
+end	
diff --git a/src/GetDataFunctions.jl b/src/GetDataFunctions.jl
@@ -422,25 +422,4 @@ function get_overall_vol_data(duration::Int64, num_exchanges::Int64)
         return DataFrame()
     end
 
-end
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+end    
diff --git a/src/PlotFunctions.jl b/src/PlotFunctions.jl
@@ -26,6 +26,45 @@ function plot_price_ma_trade_data(index::Int64, duration::Int64, window::Int64)
     return trace1, trace2, trace3, trace4, trace5
 end
 
+function plot_price_bollinger_bands(index::Int64, duration::Int64, window::Int64)
+
+    Price_df, _ , _ = get_price_data_single(currencies[index])
+
+    if duration > size(Price_df)[1]-maximum(windows)
+        duration = size(Price_df)[1]-maximum(windows)
+    end
+
+    sort!(Price_df, :Date) # oldest date first, newest at the bottom
+    Price_SMA, _ , _ = moving_averages(Price_df, duration, window)
+    Price_σ          = moving_std(Price_df, duration, window)
+
+    ################# Raw price data #################
+
+    trace1 = PlotlyJS.scatter(;x = Price_df[!,:Date][end-length(Price_SMA)+1:end], 
+                               y = Price_df[!,2][end-length(Price_SMA)+1:end],
+                               mode = "markers+lines", 
+                               name = "$(currencies[index]) price")
+
+    ################# SMA and Bollinger bands #################
+
+	trace2 = PlotlyJS.scatter(;x = Price_df[!,:Date][end-length(Price_SMA)+1:end], 
+                               y = Price_SMA, 
+                               mode = "lines", 
+                               name = "$(names(Price_df)[2]) SMA over $(window) days")
+
+	trace3 = PlotlyJS.scatter(;x = Price_df[!,:Date][end-length(Price_SMA)+1:end], 
+                               y = Price_SMA .+ 2*Price_σ, 
+                               mode = "markers", 
+                               name = "Upper band (+2σ)")
+
+    trace4 = PlotlyJS.scatter(;x = Price_df[!,:Date][end-length(Price_SMA)+1:end], 
+                               y = Price_SMA .- 2*Price_σ, 
+                               mode = "markers", 
+                               name = "Lower band (-2σ)")
+
+    return trace1, trace2, trace3, trace4
+end
+
 function plot_candle_vol_data(index::Int64, duration::Int64)
 
     # Retrieve data from various helper functions    
@@ -293,34 +332,4 @@ function plot_overall_vol_data(duration::Int64, num_exchanges::Int64 = 10)
     end
 
     return all_traces        
-end
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+end
diff --git a/test/runtests.jl b/test/runtests.jl
@@ -39,7 +39,7 @@ end
 
 ################# Test cases for moving averages #################
 
-@testset "Check if MA, MACD and signal are calculated" begin
+@testset "Check if MA, MACD + signal, σ (for Bollinger bands) are calculated" begin
 
     for currency in ["BTC", "DOT"]
 
@@ -56,8 +56,10 @@ end
 
         df_out_price = df_out_price[end-duration+1-26-9+1:end, :]
         df_ema_all = CryptoDashApp.calculate_macd(df_out_price)
-
         @test ~isempty(df_ema_all)
+
+        Price_σ = CryptoDashApp.moving_std(df_out_price, duration, window)
+        @test ~isempty(Price_σ)
 
     end
 
@@ -125,9 +127,4 @@ end
     @test ~isempty(dev_score)
     @test ~isempty(mark_score)
     @test ~isempty(fcas_rating)
-end=#
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+end=#