Curve Fitting

Curve fitting is the process of designing a financial trading system that is rigorously optimized for an exclusive set of historical data of a given asset. This is done so with the primary purpose of displaying a profit for that specific period. Traders, when developing a trading strategy, rely on two testing grounds, back-testing, and forward-testing. Back-testing is taking a set of trading rules, and applying them to the past, to judge what would have been the results had these rules been implemented then. Forward-testing is taking these same rules, and applying them in real time. Both are equally as important, since if a system doesn’t show any promise on historical data, it’s fruitless to continue in real time.If real-time testing shows constant losses despite successful back-testing, again, something’s not right.Understanding Curve FittingTechnically speaking, curve fitting is a subset of back testing, but with a twisted methodology. Traders seek to employ classical trading techniques with their own twist to see how their system performs when back testing. On the contrary, curve fitters aren’t concerned about real trading with technical analysis when back testing. Rather their interest lies in adjusting their trading rules to match the exact conditions of the market for exclusively the back-testing period, timeframe, and asset. For example, a real forex trader who trades the GBP/JPY may genuinely aim to optimize their system. This is commonly done by making some adjustments in terms of placing wider stops for this volatile currency pair based on a tried and tested tool such as the Average True Range (ATR).However, a curve fitter will just look at the GBP/JPY over a specific time period, note down its high and low for those days/hours/minutes, and then place exact profit targets within the trading range and stop losses outside the trading range. Consequently, curve fitted “systems” never perform when traded live. This is because the exact set of data, in terms of volume, spread, range, bulls and bears, support and resistance, oversold and overbought, all in relation to the exact time, etc.… are never repeated. In recent years there has been a rise in the number of vendors offering their automated trading robots, purely showing curve-fitted back-tested results. This is performed with the hope of enticing inexperienced traders. The only way to ensure the robustness of a system is to back-test and forward-test, not curve fit, as bending the rules to fit an exact set of data simply doesn’t work in real time.Any past results showing accelerating northern equity curves are merely an illusion.
Curve fitting is the process of designing a financial trading system that is rigorously optimized for an exclusive set of historical data of a given asset. This is done so with the primary purpose of displaying a profit for that specific period. Traders, when developing a trading strategy, rely on two testing grounds, back-testing, and forward-testing. Back-testing is taking a set of trading rules, and applying them to the past, to judge what would have been the results had these rules been implemented then. Forward-testing is taking these same rules, and applying them in real time. Both are equally as important, since if a system doesn’t show any promise on historical data, it’s fruitless to continue in real time.If real-time testing shows constant losses despite successful back-testing, again, something’s not right.Understanding Curve FittingTechnically speaking, curve fitting is a subset of back testing, but with a twisted methodology. Traders seek to employ classical trading techniques with their own twist to see how their system performs when back testing. On the contrary, curve fitters aren’t concerned about real trading with technical analysis when back testing. Rather their interest lies in adjusting their trading rules to match the exact conditions of the market for exclusively the back-testing period, timeframe, and asset. For example, a real forex trader who trades the GBP/JPY may genuinely aim to optimize their system. This is commonly done by making some adjustments in terms of placing wider stops for this volatile currency pair based on a tried and tested tool such as the Average True Range (ATR).However, a curve fitter will just look at the GBP/JPY over a specific time period, note down its high and low for those days/hours/minutes, and then place exact profit targets within the trading range and stop losses outside the trading range. Consequently, curve fitted “systems” never perform when traded live. This is because the exact set of data, in terms of volume, spread, range, bulls and bears, support and resistance, oversold and overbought, all in relation to the exact time, etc.… are never repeated. In recent years there has been a rise in the number of vendors offering their automated trading robots, purely showing curve-fitted back-tested results. This is performed with the hope of enticing inexperienced traders. The only way to ensure the robustness of a system is to back-test and forward-test, not curve fit, as bending the rules to fit an exact set of data simply doesn’t work in real time.Any past results showing accelerating northern equity curves are merely an illusion.

Curve fitting is the process of designing a financial trading system that is rigorously optimized for an exclusive set of historical data of a given asset.

This is done so with the primary purpose of displaying a profit for that specific period.

Traders, when developing a trading strategy, rely on two testing grounds, back-testing, and forward-testing.

Back-testing is taking a set of trading rules, and applying them to the past, to judge what would have been the results had these rules been implemented then.

Forward-testing is taking these same rules, and applying them in real time.

Both are equally as important, since if a system doesn’t show any promise on historical data, it’s fruitless to continue in real time.

If real-time testing shows constant losses despite successful back-testing, again, something’s not right.

Understanding Curve Fitting

Technically speaking, curve fitting is a subset of back testing, but with a twisted methodology.

Traders seek to employ classical trading techniques with their own twist to see how their system performs when back testing.

On the contrary, curve fitters aren’t concerned about real trading with technical analysis when back testing.

Rather their interest lies in adjusting their trading rules to match the exact conditions of the market for exclusively the back-testing period, timeframe, and asset.

For example, a real forex trader who trades the GBP/JPY may genuinely aim to optimize their system.

This is commonly done by making some adjustments in terms of placing wider stops for this volatile currency pair based on a tried and tested tool such as the Average True Range (ATR).

However, a curve fitter will just look at the GBP/JPY over a specific time period, note down its high and low for those days/hours/minutes, and then place exact profit targets within the trading range and stop losses outside the trading range.

Consequently, curve fitted “systems” never perform when traded live. This is because the exact set of data, in terms of volume, spread, range, bulls and bears, support and resistance, oversold and overbought, all in relation to the exact time, etc.… are never repeated.

In recent years there has been a rise in the number of vendors offering their automated trading robots, purely showing curve-fitted back-tested results.

This is performed with the hope of enticing inexperienced traders.

The only way to ensure the robustness of a system is to back-test and forward-test, not curve fit, as bending the rules to fit an exact set of data simply doesn’t work in real time.

Any past results showing accelerating northern equity curves are merely an illusion.

Technical Analysis

Bitcoin technical analysis & trade idea (updated! See why we are aborting)

Bitcoin technical analysis

Bitcoin technical analysis & trade idea (updated! See why we are aborting)

  • See the previous technical analysis of BTCUSD and the trade idea to short it. Since then, relative technical strength from ETHUSD and an anticipation that this may lead to a rally in crypto, led to aborting the trade idea with a small loss. Traders can follow the trade idea and update to see an example of being agile in trading and cutting your losses short, in light of new technical evidence, even if it relates to a parallel asset that should affect your trade.
ForexLive
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Technical Analysis

Ethereum technical analysis

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  • ETHUSD is fighting with the $1700 key price. The technical analysis video shows what can come next
ForexLive
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Sunday, 31/07/2022 | 10:06 GMT-0
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Technical Analysis

Google stock analysis & trade idea after earnings

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Google stock analysis & trade idea after earnings

  • See the interesting GOOG stock technical analysis with this simple trade idea (Long)
ForexLive
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Wednesday, 27/07/2022 | 05:19 GMT-0
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Cryptocurrency

Another crypto trade lost? This simple rule will probably save your ass next time.

Bitcoin chart and how intraday buyers got trapped

Another crypto trade lost? This simple rule will probably save your ass next time.

  • If you have been trading crypto, you have been there.. You are hit by a reversal and give money back to the market. What can you do instead of blaming Mister Market? This simple tip will probably save you next time.
ForexLive
ForexLive
Monday, 18/07/2022 | 21:43 GMT-0
18/07/2022 | 21:43 GMT-0
Technical Analysis

Recap of ForexLive trade idea for EURUSD and how to manage a profitable trade

Euro bought, what now?

Recap of ForexLive trade idea for EURUSD and how to manage a profitable trade

  • What does a trader do if only 1 out of 3 buy orders got filled and price rallied? Start by raising the original stop to protect profit.
ForexLive
ForexLive
Sunday, 17/07/2022 | 09:08 GMT-0
17/07/2022 | 09:08 GMT-0
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