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Time Series Classification Synthetic vs Real Financial Time Series – Part II

Time Series Classification Synthetic vs Real Financial Time Series – Part II

Posted March 30, 2020 at 9:30 am
Matthew Smith
Matthew Smith - R Blog

See the first installement in this article for instructions from Matthew Smith on which R packages and data sets you need.

I plot the returns series using ggplot.

# Plot some returns – I only plot a random sample of 20 assets for each Synthetic vs Real.

ret_plot0 <- df %>%
filter(class == 0) %>%
group_by(row_id) %>%
nest() %>%
ungroup() %>%
sample_n(20) %>%
unnest() %>%
ggplot(aes(x = variable, y = value)) +
geom_line(aes(group = factor(row_id), color = factor(row_id))) +
ggtitle(“Synthetic Financial Time Series”) +
theme_classic() +
theme(axis.text.x = element_blank(), legend.position = “bottom”, legend.title = element_blank())

ret_plot1 <- df %>%
filter(class == 1) %>%
group_by(row_id) %>%
nest() %>%
ungroup() %>%
sample_n(20) %>%
unnest() %>%
ggplot(aes(x = variable, y = value)) +
geom_line(aes(group = factor(row_id), color = factor(row_id))) +
ggtitle(“Real Financial Time Series”) +
theme_classic() +
theme(axis.text.x = element_blank(), legend.position = “bottom”, legend.title = element_blank())

plot_grid(ret_plot0, ret_plot1)

Matthew Smith - R Blog

Next I plot boxplots for the Average returns and secondly the standard deviations.

ave_box <- df %>%
group_by(class, row_id) %>%
summarise(mean = mean(value)) %>%
ggplot(aes(x = factor(class), y = mean, color = factor(class))) +
geom_boxplot(show.legend = FALSE) +
ggtitle(“Syn vs Real Average Returns”) +
xlab(“Class”) +
ylab(“Average Returns”) +
theme_tq()

sd_box <- df %>%
group_by(class, row_id) %>%
summarise(sd = sd(value)) %>%
ggplot(aes(x = factor(class), y = sd, color = factor(class))) +
geom_boxplot(show.legend = FALSE) +
ggtitle(“Syn vs Real Standard Deviations”) +
xlab(“Class”) +
ylab(“Standard Deviation”) +
theme_tq()

plot_grid(ave_box, sd_box)

Visit Matthew Smith – R Blog to see the next step in his analysis, which is calculating the Durbin-Watson statistic: https://lf0.com/post/synth-real-time-series/financial-time-series/

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This material is from Matthew Smith - R Blog and is being posted with its permission. The views expressed in this material are solely those of the author and/or Matthew Smith - R Blog and Interactive Brokers is not endorsing or recommending any investment or trading discussed in the material. This material is not and should not be construed as an offer to buy or sell any security. It should not be construed as research or investment advice or a recommendation to buy, sell or hold any security or commodity. This material does not and is not intended to take into account the particular financial conditions, investment objectives or requirements of individual customers. Before acting on this material, you should consider whether it is suitable for your particular circumstances and, as necessary, seek professional advice.

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