I made this prediction, in real time without tricks. When banks intervene you are not wrong.
We have been told that someone on YouTube is selling this system with a different name. The system is free.
https://www.forexstrategiesresources.com/renko-chart-forex-strategies/56-double-tma-renko-scalping/
https://www.forexstrategiesresources.com/renko-chart-forex-strategies/56-double-tma-renko-scalping/
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Double TMA Renko Scalping
Double TMA Renko Scalping is a renko chart trading system that is based on the idea that when crossed bands, two triangular moving averages can change market direction. So in our case when the TMA the lower band of the fast TMA crosses down to the lower band…
First of all I apologize for introducing concepts that not everyone can know, ok. Since many of you wrote to me here is a first answer regarding the examples I posted on arbitrage in this case realized in a graphic way. The answer concerns general concepts that still require knowledge of basic statistics. This answer is an input for you.
The answer concerns the basic difference between Spread trading and statistical arbitrage.
The difference between spread trading and statistical arbitrage in financial markets is subtle but significant, as both involve strategies across multiple assets. Let’s break it down:
1. Spread Trading
Spread trading involves opening long and short positions simultaneously on two correlated financial instruments, such as two stocks within the same sector (e.g., two bank stocks). The goal is to profit from temporary price differences between the two assets, rather than from their absolute movements.
For example:
Let’s say you notice that shares of Bank A and Bank B generally move in similar ways. If Bank A’s stock price rises significantly compared to Bank B, you might short Bank A and go long on Bank B, expecting that their prices will eventually realign.
The spread, or price difference between the two assets, is monitored, and the strategy aims to close positions when this spread returns to "normal" or predetermined levels.
In essence, spread trading is based on correlation and mean reversion.
2. Statistical Arbitrage
Statistical arbitrage is a more complex technique relying on quantitative analysis and mathematical models to identify short-term pricing inefficiencies among a broader set of instruments. It uses statistical algorithms to predict relative price movements and to exploit these short-term divergences.
Key characteristics:
Statistical arbitrage uses sophisticated mathematical models (such as cointegration models) to identify relationships between prices of different assets that, while not always correlated, have a historically stable or predictable relationship.
Unlike spread trading, which often focuses on two instruments, statistical arbitrage may involve portfolios with many assets (e.g., dozens or hundreds).
This strategy is more systematic and typically requires high-frequency trading (HFT) algorithms to operate on a large number of trades at very high speeds.
Fundamental Differences
Complexity and Automation: Spread trading is often simpler and can be executed manually, while statistical arbitrage requires advanced algorithms and is often automated.
Number of Assets: Spread trading generally concentrates on pairs of assets, while statistical arbitrage can involve multiple instruments simultaneously.
Type of Analysis: Spread trading leverages correlation between assets and often relies on fundamental or simpler technical analysis, while statistical arbitrage relies on quantitative models that seek complex patterns in price data.
In short, while both strategies aim to exploit relative price inefficiencies, statistical arbitrage is a more sophisticated and systematic strategy using statistical models and advanced algorithms to operate on wide portfolios, whereas spread trading focuses on pairs of correlated assets to profit from simpler price divergences.
1. Spread Trading
Spread trading involves opening long and short positions simultaneously on two correlated financial instruments, such as two stocks within the same sector (e.g., two bank stocks). The goal is to profit from temporary price differences between the two assets, rather than from their absolute movements.
For example:
Let’s say you notice that shares of Bank A and Bank B generally move in similar ways. If Bank A’s stock price rises significantly compared to Bank B, you might short Bank A and go long on Bank B, expecting that their prices will eventually realign.
The spread, or price difference between the two assets, is monitored, and the strategy aims to close positions when this spread returns to "normal" or predetermined levels.
In essence, spread trading is based on correlation and mean reversion.
2. Statistical Arbitrage
Statistical arbitrage is a more complex technique relying on quantitative analysis and mathematical models to identify short-term pricing inefficiencies among a broader set of instruments. It uses statistical algorithms to predict relative price movements and to exploit these short-term divergences.
Key characteristics:
Statistical arbitrage uses sophisticated mathematical models (such as cointegration models) to identify relationships between prices of different assets that, while not always correlated, have a historically stable or predictable relationship.
Unlike spread trading, which often focuses on two instruments, statistical arbitrage may involve portfolios with many assets (e.g., dozens or hundreds).
This strategy is more systematic and typically requires high-frequency trading (HFT) algorithms to operate on a large number of trades at very high speeds.
Fundamental Differences
Complexity and Automation: Spread trading is often simpler and can be executed manually, while statistical arbitrage requires advanced algorithms and is often automated.
Number of Assets: Spread trading generally concentrates on pairs of assets, while statistical arbitrage can involve multiple instruments simultaneously.
Type of Analysis: Spread trading leverages correlation between assets and often relies on fundamental or simpler technical analysis, while statistical arbitrage relies on quantitative models that seek complex patterns in price data.
In short, while both strategies aim to exploit relative price inefficiencies, statistical arbitrage is a more sophisticated and systematic strategy using statistical models and advanced algorithms to operate on wide portfolios, whereas spread trading focuses on pairs of correlated assets to profit from simpler price divergences.
I add that spread trading can also be done in trend, not only in divergence, exploiting volatility in our favor, for example the Nasdaq is 90% of the time faster than the S&P 500, so if I go long on the Nasdaq of $ 10,000 I will sell $ 10,000 S$P 500.
If the Nasdaq moves upwards by 1%, the SP$500 will have always moved upwards by 0.8%. So, I will earn 0.2%, and vice versa I will lose 0.2%. However, if I think that the Nasdaq will rise, I can maintain the positions and wait to go into profit without risking much.
If the Nasdaq moves upwards by 1%, the SP$500 will have always moved upwards by 0.8%. So, I will earn 0.2%, and vice versa I will lose 0.2%. However, if I think that the Nasdaq will rise, I can maintain the positions and wait to go into profit without risking much.
For those interested in these topics, you must study the basis of moving averages, variance and correlation. Then apply these concepts to the financial markets. So you need a basic text of descriptive statistics. After doing this, you need to read spread trading texts and some basic arbitrage articles (very basic).
The basic text of spread trading is this: Spread Trading and Seasonal Trading J.Ross