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Most beginner traders don't realize just how variable the p&l of even a very high-performing trading strategy is.

I simulated 10 5 year GBM processes with annual return 20% / annual vol 10%.

(Simulating a strategy within known Sharpe 2 characteristics.)

I simulated 10 5 year GBM processes with annual return 20% / annual vol 10%.

(Simulating a strategy within known Sharpe 2 characteristics.)

I plotted the path with the highest ending equity (green), median (black) and lowest (red).

All paths are from exactly the same process, with the same known return distribution.

You might think of the green line as trading a strategy with a known large edge and being lucky.

All paths are from exactly the same process, with the same known return distribution.

You might think of the green line as trading a strategy with a known large edge and being lucky.

You might think of the red line as trading a strategy with a known large edge and being unlucky.

Even when you were really lucky, you were underwater for 130 days.

When you were unlucky, you were underwater for 508 days (about 2 years)

Even when you were really lucky, you were underwater for 130 days.

When you were unlucky, you were underwater for 508 days (about 2 years)

@InBraised If you can trade for free, then your optimal trading strategy (given reasonable return estimates) would be incredibly hyperactive.

You would continuously change portfolio weights according to your latest return estimates.

You would continuously change portfolio weights according to your latest return estimates.

@InBraised In the real world, this would kill you, because trading frictions would eat away at your PnL.

So, one way to avoid hyperactive rebalancing is to only calculate your return estimates periodically (say once every day, or every week, or something).

So, one way to avoid hyperactive rebalancing is to only calculate your return estimates periodically (say once every day, or every week, or something).

@InBraised But this isn't optimal because, if your alpha is good, you want to be calculating it as often as possible. You just only want to be trading when the increase in expected returns from the new position is much better than the old position.

Examples of "elevator pitches" for retail-friendly trades, that I would find reasonable 👇👇👇

1/4

1/4

"Wealth management equity/bond rebalance flows are massive and, due to their size, may not be fully dispersed when performance differences (and therefore rebalance trades) are very large.

We might get paid for buying what they're selling around month-end"

We might get paid for buying what they're selling around month-end"

"Institutional yield enhancement programs are massive and tend to be info-insensitive sellers of volatility on an up-tick in vol.

This may keep IVs depressed in the short-term, leading to trend effects in IV on significant bad news, which we could profitably trend-follow"

This may keep IVs depressed in the short-term, leading to trend effects in IV on significant bad news, which we could profitably trend-follow"

How do I know if I have an edge?

A thread... 👇👇👇👇

I've been helping a family friend with his trading. I've given him a simple systematic strategy to trade by hand.

We can plot the distribution of historic trade returns from past trading or a backtest as a histogram.

1/n

A thread... 👇👇👇👇

I've been helping a family friend with his trading. I've given him a simple systematic strategy to trade by hand.

We can plot the distribution of historic trade returns from past trading or a backtest as a histogram.

1/n

The trade P&L is on the x-axis and the frequency (# of trades with that P&L) on the y-axis.

This is useful because it gives us a hint as to what the "edge" of our strategy might be - if we could ever truly *know* such a thing.

2/n

This is useful because it gives us a hint as to what the "edge" of our strategy might be - if we could ever truly *know* such a thing.

2/n

In this case, our strategy had positive mean and negative skew.

We saw winning trades about 58% of the time but losers were bigger, on average, than winners.

(As many things that make money tend do, regrettably)

3/n

We saw winning trades about 58% of the time but losers were bigger, on average, than winners.

(As many things that make money tend do, regrettably)

3/n

On "stationarity"...

When we talk about something being "stationary" we mean that the observations look like they could be drawn from the same "bag of observations" (distribution), regardless of what time we choose to look at.

1/5

When we talk about something being "stationary" we mean that the observations look like they could be drawn from the same "bag of observations" (distribution), regardless of what time we choose to look at.

1/5

Let me try to be helpful.

If you have some kind of factor that you think predicts future stock returns (or similar) and you are making charts like below, then here are some tips...

We'll go through an example of trying to "time" SPX with the level of VIX.

A thread 👇👇👇👇

If you have some kind of factor that you think predicts future stock returns (or similar) and you are making charts like below, then here are some tips...

We'll go through an example of trying to "time" SPX with the level of VIX.

A thread 👇👇👇👇

You get daily SPX index prices and daily VIX close data

You align them by date and plot them on dual axes, in true RealVision style.

"SPX tends to go down when VIX is high. I can therefore time an SPX allocation based on VIX. Let me share this on twitter" you say.

No. Very no.

You align them by date and plot them on dual axes, in true RealVision style.

"SPX tends to go down when VIX is high. I can therefore time an SPX allocation based on VIX. Let me share this on twitter" you say.

No. Very no.

There are two main problems with what you did:

1. The SPX price drifts. We can't directly compare the price of SPX in 2004 with its price in 2021

2. As traders, we are more interested in whether high VIX is *followed by* decreasing SPX prices, not *coincident with* them.

1. The SPX price drifts. We can't directly compare the price of SPX in 2004 with its price in 2021

2. As traders, we are more interested in whether high VIX is *followed by* decreasing SPX prices, not *coincident with* them.