ObjectiveLook forward

No more portfolios based on past performance only

Weather forecast example

How could I estimate the tomorrow raining probability using the basic statistic?

I count how many times rain in a year, for example 120 days, and I have the 33% of raining probability for tomorrow.

Do you trust about this forecast?

Weather forecast example The weather - forecasting model are very thoroughly The forecast accuracy up to 90% The model is based on the conditional probability principles

𝑓 (𝑡𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒;𝑤𝑖𝑛𝑑 𝑠𝑝𝑒𝑒𝑑 ;h𝑢𝑚𝑖𝑑𝑖𝑡𝑦 ;… )= h𝑤𝑒𝑎𝑡 𝑒𝑟 𝑓𝑜𝑟𝑒𝑐𝑎𝑠𝑡𝑖𝑛𝑔

Insight

Could we use the conditional probability in the financial market to estimate the future success of an investment?

Why not !!!

There are not only performance and volatility

Rolling time windows

Are there more attractive periods than others to invest in the stock market?

Are there any periods to get better chance to have positive returns in the next three years?

At the time of investment, can I determine in advance the probability to achieve positive returns?

Rolling time windowsWe analyze the dependence between future returns and past drawdowns

Index: S&P 500

Period: from 1967 to 2012

Frequency: monthly

S&P 500 returns Vs drawdown

3 Years Return / Risk: DD = 5%

Return

Risk

S&P 500 returns Vs drawdown

3 Years Return / Risk: DD = 10%

Return

Risk

S&P 500 returns Vs drawdown

3 Years Return / Risk: DD = 15%

Return

Risk

S&P 500 returns Vs drawdown

3 Years Return / Risk: DD = 20%

Return

Risk

S&P 500 returns Vs drawdown

3 Years Return / Risk: DD = 25%

Return

Risk

S&P 500 returns Vs drawdown

3 Years Return / Risk: DD = 30%

Return

Risk

Evidence

• When the drawdown increas in absolute value (remember the drawdown is negative) future returns increase

• Presence of mean reversion in the index price

• It makes sense to use the drawdown effect to invest

Empirical Facts on the Drawdown

Accademic validation

S&P 500 returns

Source: The Right Time to Enter (Tiziano Vargiolu University of Padova – July 2014 World Finance Conference Venice)

S&P 500 returns Vs volatility

S&P 500 returns (on y axis) Vs volatility (on x axis)

Uncorrelation between futures returns & past volatility

Source: The Right Time to Enter (Tiziano Vargiolu University of Padova – July 2014 World Finance Conference Venice)

S&P 500 returns Vs drawdown

S&P 500 returns (on y axis) Vs drawdown (on x axis)

Correlation between futures returns & past drawdown

Source: The Right Time to Enter (Tiziano Vargiolu University of Padova – July 2014 World Finance Conference Venice)

Statistics

Source: The Right Time to Enter (Tiziano Vargiolu University of Padova – July 2014 World Finance Conference Venice)

Monte Carlo Simulation

Source: The Right Time to Enter (Tiziano Vargiolu University of Padova – July 2014 World Finance Conference Venice)

Conclusion

• This fact could be causes by the presence of mean reversion in the index price

• The mathematical model that we use should incorporate mean reversion in order to reproduce significally thi effect

• For more detail about the model see the appendix

Software implementation

• DIAMAN has developed an innovative tool to estimate in advance, in the financial market, the probability to achieve positive return

• When the propability is between 49% - 75% means less probability to get positive returns

• When the propability is above 75% means high probability to get positive returns

Equity portfolio: 2007

Equity portfolio: 2009

Model efficiencyIncreasing Ex-Ante probability Increase Ex-Post positive returns

Dynamic modelThe grey columns show the period of the past crisis of 2007 and 2011

Accademic validation

Source: The Right Time to Enter (Tiziano Vargiolu University of Padova – July 2014 World Finance Conference Venice)

More detail…

Source: The Right Time to Enter (Tiziano Vargiolu University of Padova – July 2014 World Finance Conference Venice)

www.diamantech.net

www.ex-ante.it

michael.zanon@diamantech.net