sharavsambuu sharavsambuu

## checker.c
// $ cc -o checker checker.c
// $ ./checker
// $ ffmpeg -i output-%02d.ppm -r 60 output.mp4
#include <stdio.h>

int main()
{
    char buf[256];
    for (int i = 0; i < 60; ++i) {
        snprintf(buf, sizeof(buf), "output-%02d.ppm", i);

## scanner.py
"""
This script demonstrates how to build a real-time scanner that detects significant
price movements across all US stocks and ETFs using Databento's market data APIs.

Features:
- Handles entire US equities universe of ~9,000 symbols efficiently
- Median sub-ms feed delay to NY4/5 (WAN-shaped) and ~5s to start scanning
- Monitors all US stocks and ETFs for price movements exceeding a configurable threshold
- Compares current prices against previous day's closing prices
- Displays alerts when significant moves are detected

## core-strategy-1-volatility-targeting.ipynb

      
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              2 stars
            
          
                mdancho84
                / core-strategy-1-volatility-targeting.ipynb
            
            
              Created
              February 20, 2024 00:08
            
              
                Core Strategy 1: Volatility Targeting
              
          
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## cuda_11.8_installation_on_Ubuntu_22.04
#!/bin/bash

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

### to verify your gpu is cuda enable check

## 00_risk_budgeting.md

      
              6 files
            
          
              6 forks
            
          
                0 comments
              
            
              7 stars
            
          
                yhilpisch
                / 00_risk_budgeting.md
            
            
              Last active
              April 6, 2025 15:54
            
          
    Risk Parity & Budgeting

With Python
Dr. Yves J. Hilpisch | The Python Quants & The AI Machine
Python for Quant Finance Meetup, London, 16. November 2022
(short link to this Gist: http://bit.ly/pqf_risk)

  
## custom_context_menu.py
import sys

from PyQt5.QtWidgets import QApplication, QMainWindow, QTextEdit, QMenu, QAction
from PyQt5.QtGui import QCursor
from PyQt5.QtCore import Qt

class MainWindow(QMainWindow):
    def __init__(self):
        super().__init__()
        self.text_edit = QTextEdit()

## rand_augment_tfrecords.py
from imgaug import augmenters as iaa
import imgaug as ia
ia.seed(4)

import tensorflow as tf
tf.random.set_seed(666)

aug = iaa.RandAugment(n=2, m=9)
BATCH_SIZE = 224

## list.md

      
              1 file
            
          
              1032 forks
            
          
                76 comments
              
            
              2729 stars
            
          
                ih2502mk
                / list.md
            
            
              Last active
              December 5, 2025 20:37
            
              
                Quantopian Lectures Saved
              
          
    Lecture 1: Introduction to Research — [📝Lecture Notebooks] [▶️Video]

Lecture 2: Introduction to Python — [📝Lecture Notebooks] [▶️Video]

Lecture 3: Introduction to NumPy — [📝Lecture Notebooks] [▶️Video]

Lecture 4: Introduction to pandas — [📝Lecture Notebooks] [▶️Video]

Lecture 5: Plotting Data — [📝Lecture Notebooks] [[▶️Vide

  
## create_synthetic_data.py
import numpy as np
import pandas as pd
import datetime as dt

from sklearn.datasets import make_classification

def create_price_data(start_price: float = 1000.00, mu: float = .0, var: float = 1.0, n_samples: int = 1000000):

    i = np.random.normal(mu, var, n_samples)
    df0 = pd.date_range(periods=n_samples, freq=pd.tseries.offsets.Minute(), end=dt.datetime.today())

## binance-liquidation-calculator.py
#!/usr/bin/env python3
'''2021-03-26: Reverse-engineer by searching for the following terms in features*.js:
    - bracketMaintenanceMarginRate
    - cumFastMaintenanceAmount
    - bracketNotionalFloor
    - bracketNotionalCap'''


# (max) position, maintenance margin, maintenance amount
maint_lookup_table = [
	// $ cc -o checker checker.c
	// $ ./checker
	// $ ffmpeg -i output-%02d.ppm -r 60 output.mp4
	#include <stdio.h>

	int main()
	{
	char buf[256];
	for (int i = 0; i < 60; ++i) {
	snprintf(buf, sizeof(buf), "output-%02d.ppm", i);
	"""
	This script demonstrates how to build a real-time scanner that detects significant
	price movements across all US stocks and ETFs using Databento's market data APIs.

	Features:
	- Handles entire US equities universe of ~9,000 symbols efficiently
	- Median sub-ms feed delay to NY4/5 (WAN-shaped) and ~5s to start scanning
	- Monitors all US stocks and ETFs for price movements exceeding a configurable threshold
	- Compares current prices against previous day's closing prices
	- Displays alerts when significant moves are detected
	#!/bin/bash

	### steps ####
	# verify the system has a cuda-capable gpu
	# download and install the nvidia cuda toolkit and cudnn
	# setup environmental variables
	# verify the installation
	###

	### to verify your gpu is cuda enable check
	import sys

	from PyQt5.QtWidgets import QApplication, QMainWindow, QTextEdit, QMenu, QAction
	from PyQt5.QtGui import QCursor
	from PyQt5.QtCore import Qt

	class MainWindow(QMainWindow):
	def __init__(self):
	super().__init__()
	self.text_edit = QTextEdit()
	from imgaug import augmenters as iaa
	import imgaug as ia
	ia.seed(4)

	import tensorflow as tf
	tf.random.set_seed(666)

	aug = iaa.RandAugment(n=2, m=9)
	BATCH_SIZE = 224
	import numpy as np
	import pandas as pd
	import datetime as dt

	from sklearn.datasets import make_classification

	def create_price_data(start_price: float = 1000.00, mu: float = .0, var: float = 1.0, n_samples: int = 1000000):

	i = np.random.normal(mu, var, n_samples)
	df0 = pd.date_range(periods=n_samples, freq=pd.tseries.offsets.Minute(), end=dt.datetime.today())
	#!/usr/bin/env python3
	'''2021-03-26: Reverse-engineer by searching for the following terms in features*.js:
	- bracketMaintenanceMarginRate
	- cumFastMaintenanceAmount
	- bracketNotionalFloor
	- bracketNotionalCap'''


	# (max) position, maintenance margin, maintenance amount
	maint_lookup_table = [