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Last fixes
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@ -204,7 +204,7 @@ plt.show()
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# %% Monte Carlo simulation pipeline for multiple tokens ----
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# %% Monte Carlo simulation pipeline for multiple tokens ----
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# 0. set simulation params
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# 0. set simulation params
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n_simulations = int(1e4)
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n_simulations = int(1e5)
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# 1. prepare
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# 1. prepare
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quotes_data = [quotes_df.query('symbol == @s') for s in quotes_df.symbol.unique()]
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quotes_data = [quotes_df.query('symbol == @s') for s in quotes_df.symbol.unique()]
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@ -224,11 +224,10 @@ assert(
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for i in range(len(symbols_list)):
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for i in range(len(symbols_list)):
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print(f'---- Starting Monte-Carlo simulation for {symbols_list[i]} symbol ----')
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print(f'---- Starting Monte-Carlo simulation for {symbols_list[i]} symbol ----')
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prices_ms = evaluate_simulation(simulated_returns_data[i], quotes_data[i]['close'].tail(1), n_days, plot=False)
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prices_ms = evaluate_simulation(simulated_returns_data[i], quotes_data[i]['close'].tail(1), n_days, plot=False)
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plt.figure(figsize=(10, 6))
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plt.figure(figsize=(10, 6))
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plt.plot(prices_ms.sample(100, axis='columns'))
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plt.plot(prices_ms.sample(50, axis='columns'))
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plt.title(f'{symbols_list[i]} Price Simulation')
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plt.title(f'{symbols_list[i]} Price Simulation')
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plt.xlabel('Days')
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plt.xlabel('Days')
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plt.ylabel('Amount per $1')
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plt.ylabel('Amount per $1')
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