DATA SCIENCE AND VIZUALIZATION IN PYTHON

Algoritm creation processes, from data cleaning to Data vizualization and solving optimization overfitting processes.

-NUMPY
-MATPLOTLIB
-PANDAS
-SEABORN

PROFESSIONAL DEVELOPMENT FOR NinjaTrader

 STRATEGY DEVELOPMENT ON NT 8 AND METATRADER

-FUNDAMENTAL FACTOR TRADING
-ALPHA FACTOR OPTIMIZATION
-NINJATRADER PROGRAMMING

PROFESSIONAL DEVELOPMENT FOR PINE SCRIPT

Professional development for Pine Script, a programming language created by TradingView, 

-STRATEGY DEVELOPMENT 
-INDICATORS DEVELOPMENT
-STUDY DEVELOPMENT

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This indicator does a great job of finding impulses, as we know impulse is being actively traded by both contra-trend and trend following traders.

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LATEST STORIES

Strategy Design

When some market patterns stop working, others start to work.

The trader's task is to look for patterns and quickly switch from one to another

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CONSULTATIONS

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We look forward to a long cooperation, therefore customer support is our first priority

IDEA

DESIGN

DEVELOPMENT

PRODUCT

«PREDICTING THE COURSE OF A COMET IS EASIER THAN PREDICTING THE STOCK PRICE OF CITIGROUP. THE ATTRACTION, OF COURSE, IS THAT YOU CAN MAKE MORE MONEY BY SUCCESSFULLY PREDICTING A STOCK THAN A COMET »

Jim Simons

Founder of the Renaissance Technologies Hedge Fund

Learn more about Algorithmic tradingDepository arbitrage Data science in tradingIndependent researchB2B Financingbelow!!!!

TYPE OF QUANT STRATEGIES

FACTOR INVESTING STRATEGY

Factor investing is a strategy that selects securities based on attributes that have been historically associated with higher returns. This approach utilizes quantitative models to identify stocks that share one or more characteristics that have led to outperformance. Common factors include value, momentum, market capitalization, and growth, and more specific factors may include ratios such as price to book, price to free cash flow, and return on equity.

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EVENT-DRIVEN ARBITRAGE

Event-driven arbitrage is a strategy that takes advantage of price patterns that occur before or after specific events, such as earnings releases, economic data announcements, corporate actions, and regulatory changes. Portfolios are constructed by buying or selling short securities in order to lock in profits if the price action follows a typical pattern.

SYSTEMATIC GLOBAL MACRO

Systematic global macro is a strategy that utilizes quantitative analysis of the economies in different countries and regions to allocate capital to countries, regions, asset classes, and sectors that have favorable fundamentals.

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RISK PARITY FUNDS

Risk parity funds balance a portfolio's risk across asset classes based on how each asset class tends to behave in different types of environments. The goal is to offset volatility and losses in one asset class with gains in other asset classes, in order to achieve better risk-adjusted returns over time.

STATISTICAL ARBITRAGE

Statistical arbitrage is an active quant trading strategy that uses a mean reversion approach to identify mispricings based on the relationships between securities. Long and short positions are opened in related stocks in order to profit when prices revert to normal. This approach also utilizes financial ratios to identify mispriced assets.

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SMART BETA

Smart beta strategies are used to systematically manage passive investing vehicles like ETFs and mutual funds. Smart Beta strategies seek to deliver attractive risk-adjusted returns relative to standard market-cap indices by utilizing common equity factors in a transparent and cost-effective manner. sRather than using market capitalization to weight stocks, other factors can be used to improve the risk adjusted return of a portfolio.

QUANTATIVE VALUE FUNDS

Smart beta strategies are used to systematically manage passive investing vehicles such as ETFs and mutual funds. These strategies aim to deliver attractive risk-adjusted returns relative to standard market-cap indices by utilizing common equity factors in a transparent and cost-effective manner.

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SENTIMENT TRADING STRATEGY

Sentiment trading strategy involves taking positions in the market based on the consensus opinion or market sentiment. This can be momentum-based, where positions are taken based on the belief that the market will continue in its current direction, or it can be based on a contrarian approach, where positions are taken against the consensus opinion.

MACHINE LEARNING

Machine learning is a technique that involves feeding an algorithm historical data samples, including predictor variables and a target variable. The algorithm learns to use the predictor variables to predict the target variable, and can be used to improve quantitative and systematic trading strategies.

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INSIDER TRANSACTION STRATEGY

Insider transaction strategy involves analyzing the transaction patterns of corporate insiders. This approach follows the buying and selling decisions of insiders, with the belief that primary insiders have an informational advantage and will outperform the average investor over time.

ALTERNATIVE DATA STRATEGY

Alternative data strategy involves utilizing non-traditional data sources to improve quantitative and systematic trading strategies. Examples of alternative data sources include geolocation data, credit card transactions, email receipts, point-of-sale transactions, website usage, mobile app analytics, and obscure city hall records.

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WIN-ALGO
«The fool is doing something wrong all the time. The Wall Street fool thinks he should always trade».Jessie Livermore
Investor,Trader
Jessie Livermore
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RISK WARNING:

Past performance is not necessarily an indicator of future performance.

These results are based on simulated or hypothetical work results, which have certain inherent limitations. Unlike the results shown in the real performance report, these results do not reflect real trading. In addition, since these transactions have not actually been completed, the results may not be adequately or excessively offset by the influence, if any, of certain market factors, such as lack of liquidity. Modeled or hypothetical trading programs in general are also subject to the fact that they are developed based on previous indicators. None of the reported system performance reports guarantee that any account will achieve the same profit or loss ratio close to those shown.

 In addition, hypothetical trading does not involve financial risk, and the indicators of a non-hypothetical trading report cannot fully take into account the impact of financial risk in actual trading. For example, the ability to sustain losses or adhere to a certain trading program, despite trade losses, is a significant factor that can adversely affect the actual results of trading. There are many other factors related to the markets as a whole or to the implementation of any particular trading program that cannot be fully taken into account when preparing hypothetical results, each of which can adversely affect the actual results of trading.

Futures and forex trading contains substantial risk and is not for every investor. An investor could potentially lose all or more than the initial investment. Risk capital is money that can be lost without jeopardizing ones’ financial security or life style. Only risk capital should be used for trading and only those with sufficient risk capital should consider trading. Past performance is not necessarily indicative of future results.