Our risk management technology

Based on the latest findings of capital market research

In order to maintain optimal portfolio conditions in a constantly changing market, we have developed our proprietary risk management algorithm apeironprotect. It ensures that your portfolio is protected from unexpected fluctuations at all times by rule-based rebalancing. If individual components of your portfolio should fluctuate too much, our algorithm restores the target allocation again.
For this purpose, securities that are relatively expensive are sold and other securities that are relatively low priced are bought. This makes your portfolio less susceptible to fluctuations and keeps you optimally diversified at all times.

Optimal Diversification

Your portfolio is constantly monitored by our algorithm. So you always remain optimally diversified.

Lower Risk

Thanks to our risk management algorithm apeironprotect, your portfolio has a lower long-term risk.

Higher Returns

Because of our anti-cyclical rebalancing, you benefit from the scientifically proven rebalancing bonus.

Superior concept

Better returns, lower risk – our approach is clearly superior to a value-at-risk approach.

apeironprotect ensures diversification 

Even if a portfolio is balanced at the beginning, the weights of the individual securities change over time due to market fluctuations. Building blocks, which were originally only slightly mixed with the portfolio, can thus take on a significantly higher weight over the course of time. Anyone who simply buys his securities and then leaves them in the custody account, as in the classic buy-and-hold approach, is taking on unnecessary risk.
Simulated portfolio developments show that the weights of individual portfolio components can fluctuate significantly over time. Such misallocations can be avoided by rebalancing.

Buy & Hold

Annually Rebalancing

Quarterly Rebalancing

Hinweise zur Berechnung

Die Simulation basiert auf der Methodik von Ilmanen, Maloney (2015), “Portfolio Rebalancing Part 1 of 2 – Strategic Asset Allocation”. Für die Simulation wurden Portfolios bestehend aus drei hypothetischen unkorrelierten Wertpapieren mit normalverteilten Renditen gebildet. Als Annahmen für die Normalverteilung wurde ein Erwartungswert von 8% p.a. und eine Standardabweichung von 20% p.a. gewählt. Die Berechnung erfolgte auf Basis von simulierten monatlichen Renditen über zehn Jahre.
Die monatlichen Renditen berechnen sich aus den angenommenen jährlichen Renditen. Die Simulationsergebnisse dienen nur der Veranschaulichung und spiegeln keine realen Wertpapiere oder Portfolios wider.

The simulation is based on the methodology of Ilmanen, Maloney (2015), "Portfolio Rebalancing Part 1 of 2 - Strategic Asset Allocation". For the simulation, portfolios consisting of three hypothetical uncorrelated securities with normally distributed returns were formed. As assumptions for the normal distribution an expectation of 8% p.a. and a standard deviation of 20% p.a. were selected. The calculation was based on simulated monthly returns over ten years. The monthly returns are calculated from the assumed annual returns. The simulation results are for illustrative purposes only and do not reflect real securities or portfolios. Details on the calculation

It turns out that annual rebalancing leads to significantly more stable portfolio weightings. With our risk management algorithm apeironprotect, we ensure that your portfolio is balanced and diversified at all times and that the weights remain within a specified range.

N

Rebalancing helps you not to fall for classic investing errors such as buying high and selling low.

N

Ginmon will automatically rebalance your portfolio when needed so you never have to take care of it yourself.

Lower risk due to rebalancing

A rule-based rebalancing process is important to keep the risk level of a portfolio constant.

The risk profile of buy-and-hold portfolios tends to worsen over time, while that of rebalancing portfolios is more likely to stay close to the optimum. Our simulation shows that the risk of a buy-and-hold portfolio has risen significantly after ten years compared to a portfolio with annual rebalancing.

Portfolio volatility after ten years with and without rebalancing*

Simulated portfolio volatilities of a buy and hold portfolio over 10 years**

Hinweise zur Berechnung

Risiko bezeichnet hier die ex-ante Volatilität eines hypothetischen Portfolios bestehend aus 60% Aktien und 40% Anleihen. Als Approximation wurden der Vanguard Total Stock Market ETF (VTI) für den Aktienanteil und der Vanguard Total Bond Market ETF (BND) für den Anleihenanteil gewählt. Die Berechnung der Volatilitäten erfolgte auf Basis simulierter monatlicher Renditen über einen Zeitraum von zehn Jahren, unter der Annahme von normalverteilten jährlichen Renditen. Die monatlichen Renditen berechnen sich aus den angenommenen jährlichen Renditen. Die Annahmen für erwartete jährliche Rendite, Volatilität und Korrelation zwischen VTI und BND basieren auf Daten von Portfolio Visualizer von April 2009 bis Juli 2018.

Die Simulationsergebnisse dienen nur der Veranschaulichung und spiegeln keine realen Portfolios wider.
*Der Graph zeigt den Median von jeweils zwanzig simulierten ex-ante Portfoliovolatilitäten nach zehn Jahren.
**Der Graph zeigt die Entwicklung von zwanzig simulierten ex-ante Portfoliovolatilitäten für das hypothetische Buy-and-Hold-Portfolio.

Risk here means the ex-ante volatility of a hypothetical portfolio consisting of 60% equities and 40% bonds. As an approximation, the Vanguard Total Stock Market ETF (VTI) for the equity component and the Vanguard Total Bond Market ETF (BND) for the bond component were chosen. The volatilities were calculated on the basis of simulated monthly returns over a ten-year period, assuming normally distributed annual returns. The monthly returns are calculated from the assumed annual returns. Assumptions for expected annual return, volatility and correlation between VTI and BND are based on data fromPortfolio Visualizer from April 2009 to July 2018. The simulation results are for illustrative purposes only and do not reflect real portfolios.

* The graph shows the median of twenty simulated ex-ante portfolio volatilities after ten years
** The graph shows the development of twenty simulated ex-ante portfolio volatilities for the hypothetical buy-and-hold portfolio
Details on the calculation

Ginmon uses a large variety of different investment building blocks in its portfolios. A regular rebalancing with such a large number of securities would be very time-consuming for investors. Here the benefits of Ginmon’s technology-based investment approach become very clear. Because of our algorithm apeironprotect we are able to do this more efficiently than a human could.

Empirical research explains “rebalancing bonus”

Anti-cyclical rebalancing can not only reduce the risk of your portfolio, but also bring additional returns.

This additional return is known in science as a “rebalancing bonus”. Various scientific studies have empirically shown that rule-based rebalancing has better long-term returns and lower drawdowns than the classic buy-and-hold approach.

Rebalancing bonus: More return with lower drawdowns

Hinweise zur Berechnung

Die Grafik bezieht sich auf Ilmanen, Maloney (2015), “Portfolio Rebalancing Part 1 of 2 – Strategic Asset Allocation”. Die Autoren betrachten in ihrer Studie ein globales Portfolio bestehend aus Aktien, Anleihen und Rohstoffen über den Zeitraum 1972-2014. Ähnliche Ergebnisse lassen sich aber auch in der Studie “Empirical Analysis of Rebalancing Strategies” des norwegischen Staatsfonds finden (2012).

Weitere wissenschaftliche Arbeiten, die sich mit dem “Rebalancing-Bonus” befassen, finden Sie hier:

Nardon, Kiskiras (2013), Portfolio Rebalancing: A stable source of alpha

Bernstein (1997), Rebalancing Bonus: Theory and Practise

The chart refers to Ilmanen, Maloney (2015), "Portfolio Rebalancing Part 1 of 2 - Strategic Asset Allocation". In their study, the authors consider a global portfolio consisting of stocks, bonds and commodities over the period 1972-2014. Similar results can also be found in the study Empirical Analysis of Rebalancing Strategies of the Norwegian State Fund (2012).

Further scientific papers dealing with the "Rebalancing-Bonus" can be found here:
Nardon, Kiskiras (2013), Portfolio Rebalancing: A stable source of alpha
Bernstein (1997), Rebalancing Bonus: Theory and Practise
Details on the chart

Rebalancing is superior to the value-at-risk approach

A rule-based rebalancing approach is also convincing in comparison to other investment strategies such as the value-at-risk approach (VaR).

In a study, the Munich Institute for Asset Buildings examined the differences between rebalancing-based risk management and risk management with fluctuating equity ratios (value-at-risk). The result: Rebalancing leads to higher returns and the probability of extreme losses is significantly lower.

Expected return

Probability of losing -10% or more

The lower return on the VaR approach is explained by the researchers’ significantly higher transaction costs. Again it is shown that frequent trading offers no added value – on the contrary! It also shows that an interim loss of -10% for a VaR is much more likely than for a rebalancing approach. The alleged advantage of a volatility control can therefore not be proven scientifically.

Our risk management technology

Based on the latest findings of capital market research

In order to maintain optimal portfolio conditions in a constantly changing market, we have developed our proprietary risk management algorithm apeironprotect. It ensures that your portfolio is protected from unexpected fluctuations at all times by rule-based rebalancing. If individual components of your portfolio should fluctuate too much, our algorithm restores the target allocation again.
For this purpose, securities that are relatively expensive are sold and other securities that are relatively low priced are bought. This makes your portfolio less susceptible to fluctuations and keeps you optimally diversified at all times.

Optimal Diversification

Your portfolio is constantly monitored by our algorithm. So you always remain optimally diversified.

Lower Risk

Thanks to our risk management algorithm apeironprotect, your portfolio has a lower long-term risk.

Hugher returns

Because of our anti-cyclical rebalancing, you benefit from the scientifically proven rebalancing bonus.

Superior concept

Better returns, lower risk – our approach is clearly superior to a value-at-risk approach.

apeironprotect ensures diversification

Even if a portfolio is balanced at the beginning, the weights of the individual securities change over time due to market fluctuations. Building blocks, which were originally only slightly mixed with the portfolio, can thus take on a significantly higher weight over the course of time. Anyone who simply buys his securities and then leaves them in the custody account, as in the classic buy-and-hold approach, is taking on unnecessary risk.

Simulated portfolio developments show that the weights of individual portfolio components can fluctuate significantly over time. Such misallocations can be avoided by rebalancing.

Buy & Hold

Annual Rebalancing

Quarterly Rebalancing

Details on the calculation

The simulation is based on the methodology of Ilmanen, Maloney (2015), “Portfolio Rebalancing Part 1 of 2 – Strategic Asset Allocation”. For the simulation, portfolios consisting of three hypothetical uncorrelated securities with normally distributed returns were formed. As assumptions for the normal distribution an expectation of 8% p.a. and a standard deviation of 20% p.a. were selected. The calculation was based on simulated monthly returns over ten years. The monthly returns are calculated from the assumed annual returns. The simulation results are for illustrative purposes only and do not reflect real securities or portfolios.

It turns out that annual rebalancing leads to significantly more stable portfolio weightings. With our risk management algorithm apeironprotect, we ensure that your portfolio is balanced and diversified at all times and that the weights remain within a specified range.

N

Rebalancing helps you not to fall for classic investing errors such as buying high and selling low.

N

Ginmon will automatically rebalance your portfolio when needed so you never have to take care of it yourself.

Lower risk due to rebalancing

A rule-based rebalancing process is important to keep the risk level of a portfolio constant.

The risk profile of buy-and-hold portfolios tends to worsen over time, while that of rebalancing portfolios is more likely to stay close to the optimum. Our simulation shows that the risk of a buy-and-hold portfolio has risen significantly after ten years compared to a portfolio with annual rebalancing.

Portfolio volatility after ten years with and without rebalancing*

Simulated portfolio volatilities of a buy and hold portfolio over 10 years**

Details on the calculation

Risk here means the ex-ante volatility of a hypothetical portfolio consisting of 60% equities and 40% bonds. As an approximation, the Vanguard Total Stock Market ETF (VTI) for the equity component and the Vanguard Total Bond Market ETF (BND) for the bond component were chosen. The volatilities were calculated on the basis of simulated monthly returns over a ten-year period, assuming normally distributed annual returns. The monthly returns are calculated from the assumed annual returns. Assumptions for expected annual return, volatility and correlation between VTI and BND are based on data from Portfolio Visualizer from April 2009 to July 2018.

The simulation results are for illustrative purposes only and do not reflect real portfolios.
*The graph shows the median of twenty simulated ex-ante portfolio volatilities after ten years.
**The graph shows the development of twenty simulated ex-ante portfolio volatilities for the hypothetical buy-and-hold portfolio.

Risiko bezeichnet hier die ex-ante Volatilität eines hypothetischen Portfolios bestehend aus 60% Aktien und 40% Anleihen. Als Approximation wurden der Vanguard Total Stock Market ETF (VTI) für den Aktienanteil und der Vanguard Total Bond Market ETF (BND) für den Anleihenanteil gewählt. Die Berechnung der Volatilitäten erfolgte auf Basis simulierter monatlicher Renditen über einen Zeitraum von zehn Jahren, unter der Annahme von normalverteilten jährlichen Renditen. Die monatlichen Renditen berechnen sich aus den angenommenen jährlichen Renditen. Die Annahmen für erwartete jährliche Rendite, Volatilität und Korrelation zwischen VTI und BND basieren auf Daten von Portfolio Visualizer von April 2009 bis Juli 2018. Die Simulationsergebnisse dienen nur der Veranschaulichung und spiegeln keine realen Portfolios wider.

*Der Graph zeigt den Median von jeweils zwanzig simulierten ex-ante Portfoliovolatilitäten nach zehn Jahren.
**Der Graph zeigt die Entwicklung von zwanzig simulierten ex-ante Portfoliovolatilitäten für das hypothetische Buy-and-Hold-Portfolio.
Hinweis zur Berechnung

Ginmon uses a large variety of different investment building blocks in its portfolios. A regular rebalancing with such a large number of securities would be very time-consuming for investors. Here the benefits of Ginmon’s technology-based investment approach become very clear. Because of our algorithm apeironprotect we are able to do this more efficiently than a human could.

Empirical research explains “rebalancing bonus”

Anti-cyclical rebalancing can not only reduce the risk of your portfolio, but also bring additional returns.

This additional return is known in science as a “rebalancing bonus”. Various scientific studies have empirically shown that rule-based rebalancing has better long-term returns and lower drawdowns than the classic buy-and-hold approach.

Rebalancing bonus: More return with lower drawdowns

Hinweise zur Berechnung

The chart refers to Ilmanen, Maloney (2015), “Portfolio Rebalancing Part 1 of 2 – Strategic Asset Allocation”. In their study, the authors consider a global portfolio consisting of stocks, bonds and commodities over the period 1972-2014. Similar results can also be found in the study Empirical Analysis of Rebalancing Strategies of the Norwegian State Fund (2012).
Further scientific papers dealing with the “Rebalancing-Bonus” can be found here:
Nardon, Kiskiras (2013), Portfolio Rebalancing: A stable source of alpha
Bernstein (1997), Rebalancing Bonus: Theory and Practise

Die Grafik bezieht sich auf Ilmanen, Maloney (2015), “Portfolio Rebalancing Part 1 of 2 - Strategic Asset Allocation”. Die Autoren betrachten in ihrer Studie ein globales Portfolio bestehend aus Aktien, Anleihen und Rohstoffen über den Zeitraum 1972-2014. Ähnliche Ergebnisse lassen sich aber auch in der Studie “Empirical Analysis of Rebalancing Strategies” des norwegischen Staatsfonds finden (2012).

Weitere wissenschaftliche Arbeiten, die sich mit dem “Rebalancing-Bonus” befassen, finden Sie hier:
Nardon, Kiskiras (2013), Portfolio Rebalancing: A stable source of alpha
Bernstein (1997), Rebalancing Bonus: Theory and Practise
Hinweis zur Berechnung

Rebalancing is superior to the value-at-risk approach

A rule-based rebalancing approach is also convincing in comparison to other investment strategies such as the value-at-risk approach (VaR).

In a study, the Munich Institute for Asset Buildings examined the differences between rebalancing-based risk management and risk management with fluctuating equity ratios (value-at-risk). The result: Rebalancing leads to higher returns and the probability of extreme losses is significantly lower.

Expected return

Probability of losing -10% or more

The lower return on the VaR approach is explained by the researchers’ significantly higher transaction costs. Again it is shown that frequent trading offers no added value – on the contrary! It also shows that an interim loss of -10% for a VaR is much more likely than for a rebalancing approach. The alleged advantage of a volatility control can therefore not be proven scientifically.

Our risk management technology

Based on the latest findings of capital market research

In order to maintain optimal portfolio conditions in a constantly changing market, we have developed our proprietary risk management algorithm apeironprotect. It ensures that your portfolio is protected from unexpected fluctuations at all times by rule-based rebalancing. If individual components of your portfolio should fluctuate too much, our algorithm restores the target allocation again.

For this purpose, securities that are relatively expensive are sold and other securities that are relatively low priced are bought. This makes your portfolio less susceptible to fluctuations and keeps you optimally diversified at all times.

Optimal Diversification

Your portfolio is constantly monitored by our algorithm. So you always remain optimally diversified.

Lower Risk

Thanks to our risk management algorithm apeironprotect, your portfolio has a lower long-term risk.

Higher Returns

Because of our anti-cyclical rebalancing, you benefit from the scientifically proven rebalancing bonus.

Superior concept

Better returns, lower risk – our approach is clearly superior to a value-at-risk approach.

apeironprotect ensures diversification

Even if a portfolio is balanced at the beginning, the weights of the individual securities change over time due to market fluctuations. Building blocks, which were originally only slightly mixed with the portfolio, can thus take on a significantly higher weight over the course of time. Anyone who simply buys his securities and then leaves them in the custody account, as in the classic buy-and-hold approach, is taking on unnecessary risk.

Simulated portfolio developments show that the weights of individual portfolio components can fluctuate significantly over time. Such misallocations can be avoided by rebalancing.

Buy & Hold

Annual Rebalancing

Quaterly Rebalancing

Details on the calculation

The simulation is based on the methodology of Ilmanen, Maloney (2015), “Portfolio Rebalancing Part 1 of 2 – Strategic Asset Allocation”. For the simulation, portfolios consisting of three hypothetical uncorrelated securities with normally distributed returns were formed. As assumptions for the normal distribution an expectation of 8% p.a. and a standard deviation of 20% p.a. were selected. The calculation was based on simulated monthly returns over ten years. The monthly returns are calculated from the assumed annual returns. The simulation results are for illustrative purposes only and do not reflect real securities or portfolios.

It turns out that annual rebalancing leads to significantly more stable portfolio weightings. With our risk management algorithm apeironprotect, we ensure that your portfolio is balanced and diversified at all times and that the weights remain within a specified range.

N

Rebalancing helps you not to fall for classic investing errors such as buying high and selling low.

N

Ginmon will automatically rebalance your portfolio when needed so you never have to take care of it yourself.

Lower risk due to rebalancing

A rule-based rebalancing process is important to keep the risk level of a portfolio constant.

The risk profile of buy-and-hold portfolios tends to worsen over time, while that of rebalancing portfolios is more likely to stay close to the optimum. Our simulation shows that the risk of a buy-and-hold portfolio has risen significantly after ten years compared to a portfolio with annual rebalancing.

Portfolio volatility after ten years with and without rebalancing*

Simulated portfolio volatilities of a buy and hold portfolio over 10 years**

Details on the calculation

Risk here means the ex-ante volatility of a hypothetical portfolio consisting of 60% equities and 40% bonds. As an approximation, the Vanguard Total Stock Market ETF (VTI) for the equity component and the Vanguard Total Bond Market ETF (BND) for the bond component were chosen. The volatilities were calculated on the basis of simulated monthly returns over a ten-year period, assuming normally distributed annual returns. The monthly returns are calculated from the assumed annual returns. Assumptions for expected annual return, volatility and correlation between VTI and BND are based on data from Portfolio Visualizer from April 2009 to July 2018.

The simulation results are for illustrative purposes only and do not reflect real portfolios.
*The graph shows the median of twenty simulated ex-ante portfolio volatilities after ten years.
**The graph shows the development of twenty simulated ex-ante portfolio volatilities for the hypothetical buy-and-hold portfolio.

Ginmon uses a large variety of different investment building blocks in its portfolios. A regular rebalancing with such a large number of securities would be very time-consuming for investors. Here the benefits of Ginmon’s technology-based investment approach become very clear. Because of our algorithm apeironprotect we are able to do this more efficiently than a human could.

Empirical research explains “rebalancing bonus”

Anti-cyclical rebalancing can not only reduce the risk of your portfolio, but also bring additional returns.

This additional return is known in science as a “rebalancing bonus”. Various scientific studies have empirically shown that rule-based rebalancing has better long-term returns and lower drawdowns than the classic buy-and-hold approach.

Rebalancing bonus: More return with lower drawdowns

Details on the chart

The chart refers to Ilmanen, Maloney (2015), “Portfolio Rebalancing Part 1 of 2 – Strategic Asset Allocation”. In their study, the authors consider a global portfolio consisting of stocks, bonds and commodities over the period 1972-2014. Similar results can also be found in the study Empirical Analysis of Rebalancing Strategies of the Norwegian State Fund (2012).
Further scientific papers dealing with the “Rebalancing-Bonus” can be found here:
Nardon, Kiskiras (2013), Portfolio Rebalancing: A stable source of alpha
Bernstein (1997), Rebalancing Bonus: Theory and Practise

Rebalancing is superior to the value-at-risk approach

A rule-based rebalancing approach is also convincing in comparison to other investment strategies such as the value-at-risk approach (VaR).

In a study, the Munich Institute for Asset Buildings examined the differences between rebalancing-based risk management and risk management with fluctuating equity ratios (value-at-risk). The result: Rebalancing leads to higher returns and the probability of extreme losses is significantly lower.

Expected return

Probability of losing -10% or more

The lower return on the VaR approach is explained by the researchers’ significantly higher transaction costs. Again it is shown that frequent trading offers no added value – on the contrary! It also shows that an interim loss of -10% for a VaR is much more likely than for a rebalancing approach. The alleged advantage of a volatility control can therefore not be proven scientifically.

  

 

 

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