ideas of trading strategies from AlgoQuant

[aqtrader]

I just came across AlgoQuant. I know nothing about their software but from the website I saw they linked to a few interesting research papers on trading strategies: http://numericalmethod.com/quantitative-trading-strategies/

Moreover, the model proposes a way to use intraday volatility to estimate which of the two regimes we are in -

• mean-reversion, or
• momentum

Combining the estimated expected returns with the regime indicator, we do mean-reversion when the intraday volatility is small, and trend following when the intraday volatility is big.

How can we believe any published trading ideas are really effective otherwise why they do not take the advantage to trade themselves?

 

[kut2k2]

How can we believe any published trading ideas are really effective ...?

Backtesting. The same way you determine whether your own trading ideas are effective. Every now and then something useful leaks out into the public domain. Only testing determines whether this is so, on a case-by-case basis.

 

[optstack]

I just came across AlgoQuant. I know nothing about their software but from the website I saw they linked to a few interesting research papers on trading strategies:

How can we believe any published trading ideas are really effective otherwise why they do not take the advantage to trade themselves?

Backtesting is definitely a great start to verifying whether these trading strategies are effective. However, even if the backtest results are impressive, I would start off small and verify how the strategy works in live market conditions, before allocating any significant money to the strategy.

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[jamesmawm]

the quoted conditions is called volatility ratio. VR>1.0 is trending, VR=1.0 is random walk/Brownian, VR<1.0 is mean-reverting. Commonly used in statistical arbitrage. But volatility is persistent, and using statistical arbitrage without sound econometric fundamentals is akin to suicide.