random_price.cpp File Reference

Random price generator for stock market simulation. More...

#include "random_price.h"
#include <algorithm>
#include <cstdlib>
#include <random>
#include <iostream>

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Functions
std::map< stock_modifiers, float >	getProcessedModifiers (Stock stock)
	Get the processed modifiers for the stock.
float	init_sd (void)
	Initialize the standard deviation of the stock price.
float	init_stock_price (int price_profile)
	Initialize starting stock price.
float	percentage_change_price (Stock stock)
	Calculate the percentage change of the stock price.
unsigned int	random_integer (unsigned int max_integer)
	python randint like function

Detailed Description

Random price generator for stock market simulation.

Definition in file random_price.cpp.

Function Documentation

getProcessedModifiers()

std::map< stock_modifiers, float > getProcessedModifiers

(

Stock

stock

)

Get the processed modifiers for the stock.

Parameters

stock

the stock to get the processed modifiers

Returns

the processed modifiers

Note

the values of the processed modifiers are final values that will be used to calculate the percentage change of the stock price

Definition at line 54 of file random_price.cpp.

                                                                  {
    float trueMean = meanMultiplier * (stock.get_total_attribute(mean));
    float trueSD = sdMultiplier * (stock.get_total_attribute(standard_deviation));
    unsigned int rounds_passed = stock.get_history_size();
    if (stock.get_price() < stock.get_initial_price() / 10) {
        // Force the return of a significantly higher mean normal dist, by a bit over
        // doubling the price.
        trueMean += 200;
    }
    else if (stock.get_price() < stock.get_initial_price() / 7) {
        trueMean += 100;
    }
    /* There is a upper limit and lower limit that the realisation of the % change must
     * fall between. As each round pass we allow for more and more chaotic behaviour by
     * making the bounds less tight.
     * Just for fun (chaotic evil smirk). Upon devastating events which leads to
     * a stock price only 10 % left of it's initial, we increase mean to prevent a game
     * over. Upon we are 90.32% sure the bounds would be wrong we bump the mean.
     */
    // temp is the percentage difference between the initial price and the current price
    // of the stock.
    float temp = 100 * std::abs(stock.get_initial_price() - stock.get_price()) /
                 stock.get_price();
    float upper_lim = stock.get_base_attribute(upper_limit) +
                      stock.get_event_attribute(upper_limit) * upperLimitMultiplier +
                      std::min(static_cast<int>(rounds_passed / 3), 10) + temp;
    float lower_lim = stock.get_base_attribute(lower_limit) +
                      stock.get_event_attribute(lower_limit) * lowerLimitMultiplier -
                      std::min(static_cast<int>(rounds_passed / 3), 10) - temp;
    // Standardize the upper and lower limit
    float zScoreUpLimit = (upper_limit - trueMean) / trueSD;
    float zScoreLowLimit = (lower_limit - trueMean) / trueSD;
    for (int i = 0; i < 10; i++) {
        if (zScoreLowLimit > 1.3) {
            // Very likely to fail lower_limit; about 90.32%; which means it is too low
            // and should realize at higher value;
            trueMean += meanMultiplier;
            zScoreLowLimit = (lower_limit - trueMean - 0.1) / trueSD;
        }
        if (zScoreUpLimit < -1.3) {
            // Converse
            // Reason: for N(0,1), probability of exceeed 1.3 is less that 10%
            trueMean -= meanMultiplier;
            zScoreUpLimit = (upper_limit - trueMean + 0.1) / trueSD;
        }
    }
    // -100% is not applicable for a stock price, so we set it to -90%.
    if (lower_lim < -90) {
        lower_lim = -90;
    }
    else if (lower_lim > defaultLowerLimit) {
        lower_lim = defaultLowerLimit;
    }
    if (upper_lim < defaultUpperLimit) {
        upper_lim = defaultUpperLimit;
    }
    return {{standard_deviation, trueSD}, {mean, trueMean}, {lower_limit, lower_lim},
        {upper_limit, upper_lim}};
}

References defaultLowerLimit, defaultUpperLimit, Stock::get_base_attribute(), Stock::get_event_attribute(), Stock::get_history_size(), Stock::get_initial_price(), Stock::get_price(), Stock::get_total_attribute(), lower_limit, lowerLimitMultiplier, mean, meanMultiplier, sdMultiplier, standard_deviation, upper_limit, and upperLimitMultiplier.

Referenced by percentage_change_price(), and print_table().

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init_sd()

float init_sd

(

void

)

Initialize the standard deviation of the stock price.

Definition at line 36 of file random_price.cpp.

                    {
    std::random_device rd;
    std::mt19937 gen(rd());
    // The old distribution was 0.5, 0.5.
    // After applying std::abs(), the distribution is not symmetric anymore.
    std::normal_distribution<float> distribution(0, 0.5);
    return std::abs(distribution(gen)) + 0.5;
}

Referenced by Stock::Stock().

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init_stock_price()

float init_stock_price

(

int

price_profile

)

Initialize starting stock price.

a	mean	s.d.
1	5	2
2	50	20
3	150	50

Parameters

a	the profile of the stock price

Returns

the initial stock price

Definition at line 23 of file random_price.cpp.

                                          {
    std::random_device rd;
    std::mt19937 gen(rd());
    std::normal_distribution<float> distribution(5.0, 2.0);
    if (price_profile == 2) {
        distribution.param(std::normal_distribution<float>::param_type(50.0, 20.0));
    }
    if (price_profile == 3) {
        distribution.param(std::normal_distribution<float>::param_type(150.0, 50.0));
    }
    return std::abs(distribution(gen));
}

Referenced by Stock::Stock().

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percentage_change_price()

float percentage_change_price

(

Stock

stock

)

Calculate the percentage change of the stock price.

Returns

the percentage change of the stock price

Parameters

stock

the stock to calculate the percentage change

Definition at line 114 of file random_price.cpp.

                                           {
    std::random_device rd;
    std::mt19937 gen(rd());
    std::map<stock_modifiers, float> _modifiers = getProcessedModifiers(stock);
    std::normal_distribution<float> distribution(
        _modifiers[mean], _modifiers[standard_deviation]);
    // std::cout << offset << " " << sd << " " << lower_lim << " " << upper_lim <<
    // std::endl; Implementing a max loop here so will not be infinite if there is a
    // fault.
    for (unsigned int max_loop = 0; max_loop < 100; max_loop++) {
        float x = distribution(gen);
        if (x > _modifiers[lower_limit] && x < _modifiers[upper_limit]) {
            return x / std::pow(2, stock.get_split_count());
        }
    }
    // Need to have some stocastic behavour against a fault.
    float stocastics[12] = {0.95507, -0.74162, 1.642, -0.94774, -0.80314, 1.7885,
        -0.09846, 1.4693, 0.19288, -1.70222, 1.20933, -0.71088};
    return stocastics[random_integer(12)];
}

References Stock::get_split_count(), getProcessedModifiers(), lower_limit, mean, random_integer(), standard_deviation, and upper_limit.

Referenced by Stock::next_round().

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random_integer()

unsigned int random_integer

(

unsigned int

max_integer

)

python randint like function

Parameters

max_integer

the maximum integer + 1 that can be returned

Returns

a random integer in [0, max_integer - 1]

Definition at line 45 of file random_price.cpp.

                                                      {
    // Discrete uniform distribution
    // like python randint
    std::random_device rd;
    std::mt19937 gen(rd());
    std::uniform_int_distribution<unsigned int> distribution(0, max_integer - 1);
    return distribution(gen);
}

Referenced by Stock::Stock(), new_events_next_round(), percentage_change_price(), pick_events(), and pickUniqueNames().

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