I have adapted to R a python code to plot these charts:

I simulate the regression lines with x_plot <- seq(min(market_excess_return), max(market_excess_return), length.out = 100)

However, when I plot the regression lines to include them in the chart I am capable to include only one fitted line with geom_abline(), resulting this:

How can I include the x_plot object?

I provide the full code:

library(ggplot2)
library(dplyr)
library(brms) # For Bayesian regression
library(bayesplot) # For plotting Bayesian analysis results

set.seed(42)
size <- 200
Rf <- 0.02
ERm <- 0.1
beta <- 1.5
sigma <- 0.05

ERm_samples <- rnorm(size, ERm, sigma)

epsilon <- rnorm(size, 0, sigma)
ERi_samples <- Rf + beta * (ERm_samples - Rf) + epsilon

market_excess_return <- ERm_samples - Rf
asset_excess_return <- ERi_samples - Rf

data_capm <- data.frame(market_excess_return=market_excess_return, asset_excess_return=asset_excess_return)

ggplot(data_capm, aes(x=market_excess_return, y=asset_excess_return)) +
  geom_point(aes(color='Sampled Data')) +
  labs(x='Market Excess Return', y='Asset Excess Return', title='Generated CAPM Data') +
  theme_minimal()

# Bayesian regression using brms
model_capm <- brm(asset_excess_return ~ market_excess_return, data = data_capm, 
                  family = gaussian(), prior = c(
                    prior(normal(0, 20), class = Intercept),
                    prior(normal(0, 20), class = b),
                    prior(cauchy(0, 10), class = sigma)
                  ))

# Plotting the trace
trace_capm <- as.mcmc(model_capm) 
bayesplot::mcmc_trace(trace_capm)

# Posterior predictive checks
#posterior_intercept <- fitted(model_capm)$Estimate[1,]
#posterior_slope <- fitted(model_capm)$Estimate[2,]
posterior_intercept <- fitted(model_capm)[1, "Estimate"]
posterior_slope <- fitted(model_capm)[2, "Estimate"]

x_plot <- seq(min(market_excess_return), max(market_excess_return), length.out = 100)

ggplot(data_capm, aes(x=market_excess_return, y=asset_excess_return)) +
  geom_point(alpha=0.5, color = 'tomato') +
  geom_abline(intercept=mean(posterior_intercept), 
              slope=mean(posterior_slope), 
              color="blue", 
              linetype="dashed") +
  labs(x='Market Excess Return', 
       y='Asset Excess Return', 
       title='Posterior Predictive Regression Lines with Observed Data') +
  theme_minimal()