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How Correlation and Shorting Affect Portfolio Volatility

Article Quant Q&A · Author: elemolotiv

Summary

The document asks whether two assets with equal return volatility can be combined into a product with greater percentage-return volatility, without simply using cash leverage. It considers a long-only linear combination and derives its variance from the assets’ volatilities, weights, and return correlation. Under the stated equal-volatility assumption and weights between zero and one, the combination cannot exceed either component’s volatility.

Allowing a weight outside that range means shorting one asset to fund exposure to the other, which can raise volatility through relative positioning. Another answer notes that a spread option may be more volatile than either underlying and mentions volatility of volatility as a possible feature to consider. These are conceptual suggestions; the document does not analyze transaction costs, specify a particular product, or demonstrate that higher volatility creates a trading edge.

Key ideas

  • Portfolio return variance depends on asset weights and the correlation between returns.
  • A long-only mix of two assets with equal volatility cannot exceed their individual volatility under the stated setup.
  • Shorting one asset to increase exposure to another can raise portfolio volatility.
  • Spread options may have greater volatility than either underlying asset.

Tags

Full text
# How to create a volatile market, by combining less volatile markets?


# How to create a volatile market, by combining less volatile markets?












This might be against the law of gravity, but I'll give a try 🙂

Is there a way to combine two financial products $p_1$ and $p_2$, into a single product $p_c$ that is more volatile than its components?

Mathematically, if the daily returns of the original products are:

$$r_1\sim \mathcal{N}(\mu,\,\sigma^{2})$$ $$r_2\sim \mathcal{N}(\mu,\,\sigma^{2})$$

Can I build a financial product whose daily returns are:

$$r_c\sim \mathcal{N}(\mu_c,\,\sigma_c^{2})$$ $$\sigma_c > \sigma$$

Careful:

- I am not looking to increase volatility of absolute returns. (e.g. returns in USD). That is easy, just use leverage. But with leverage come proportionally higher transaction costs. So you don't have an extra edge in trading.

- I am looking to increase volatility of relative returns (e.g. percentage returns). I want to obtain higher volatility, at stable transaction costs. That would be an extra hedge in trading.

## Answer by bhutes (score 2)

https://quant.stackexchange.com/a/46200

Throw in correlation as the additional variable.

Similarly, volofvol could be another candidate to play with.

A spread option could have a larger volatility than either of the two underliers.

## Answer by Daneel Olivaw (score 2)

https://quant.stackexchange.com/a/46205

Let $X_1$ and $X_2$ be your two assets and $C$ your financial product. For now we only assume products which are a linear combination of $X_1$ and $X_2$ with no shorting allowed, hence: $$\begin{align} & C=\alpha X_1 + (1-\alpha)X_2 \\ & 0\leq \alpha \leq 1 \end{align}$$ Letting $\rho$ be the correlation between returns $r_1$ and $r_2$, we have: $$\begin{align} \sigma_c^2&=\alpha^2\sigma^2+(1-\alpha)^2\sigma^2+2\alpha(1-\alpha)\sigma^2\rho \\ &=(1-2\alpha+2\alpha^2)\sigma^2+2\alpha(1-\alpha)\sigma^2\rho \end{align}$$ You are asking under which conditions: $$\sigma_c^2>\sigma^2$$ Namely: $$(1-2\alpha+2\alpha^2)+2\alpha(1-\alpha)\rho>1$$ Rearranging and letting $\theta=2(1-\rho)\geq0$: $$\theta\alpha^2-\theta\alpha+1>1$$ Namely: $$\theta\alpha(\alpha-1)>0$$ but there is no value of $\alpha$ for which this inequality is enforced given our initial constraint $0\leq \alpha\leq1$. On the other hand, if you allow short-selling, namely $\alpha$ can take values lower than $0$ or higher than $1$, so some sort of leverage (where leverage in one asset is financed by shorting the other one), you observe that you manage to increase the volatility of the product $\sigma_c$ with respect to the underlying volatility $\sigma$.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.