Tag: Volatility

Implied Volatility: Data, Indicators and Usage

Implied volatility is the market’s expectation of future moves. This article will show you a simple way to access Refinitiv Eikon data in Tradesignal, visualise it and scan for exceptional volatility in stocks and ETFs.¬† Replacing historical volatility by implied volatility will give you new insights to risk management and options trading.

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Sharpe Ratio comparison of two assets

Sharpe Ratio Indicator: Scan for Performance

The Sharpe Ratio is a measure for risk-adjusted returns, developed by Nobel Laureate William F. Sharpe in 1966. It describes the volatility-adjusted excess returns of an asset over a risk-free return. This article highlights the thoughts behind the Sharpe Ratio formula and some practical applications of it when selecting different asset classes.

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Outperformance Portfolio Backtest

Outperformance: Find the right Stocks to beat the Index

Whenever you try to beat an index you will have to be invested in an asset which outperforms your benchmark. This article is about how to calculate outperformance and how to make use of it. In its most simple definition outperformance just means that one asset is performing better than an other asset. But this simple definition is not enough for investors.

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Volatility projection Indicator

Volatility Projection

Today the market moves up, tomorrow it might move down, but is this of any importance or just random noise? This volatility projection indicator will tell you if there is something exceptional happening. Standard Deviation and Volatility Projection The standard deviation of market movements is a widely used measure to define exceptional events on the market. An example: Bollinger Bands 

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KAMA Threshold on the FTSE

How KAMA Threshold adjusts to Market Volatility

A KAMA Threshold is a combination of a threshold above a special type of moving average – the KAMA. KAMA stands for the Kaufman’s Adaptive Moving Average. The KAMA is a type of moving average which aids in the reduction of fluctuations in data. It adjusts to market volatility by lengthening and shortening depending on market conditions. When the market

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