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Converting Asset Holdings into Wealth-Weighted Portfolio Exposures

Article Quant Q&A · Author: Phun

Summary

The question concerns a stochastic wealth equation that appears to produce inconsistent expressions when a portfolio strategy is substituted into it. The answer identifies a distinction between the number of asset shares held and the fraction of wealth allocated to those assets. If the strategy variable denotes shares, multiplying it by asset prices and dividing by portfolio wealth converts it into a wealth-weighted exposure.

That conversion clarifies why the paper’s expression uses portfolio proportions in the wealth dynamics rather than the raw holdings. The answer points to the paper’s definition of the transformed strategy and its optimal form as support. This is a focused explanation of notation and portfolio accounting, not a derivation of the full stochastic control solution; it assumes the paper’s definitions and setup are otherwise valid.

Key ideas

  • A trading strategy measured in shares is different from one measured as a fraction of portfolio wealth.
  • Multiplying share holdings by asset prices gives the market value invested in each asset.
  • Dividing those market values by wealth yields portfolio weights for expressing wealth dynamics.
  • The distinction between holdings and weights resolves the apparent mismatch in the stochastic equation.

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Full text
# Problems to understand a stochastic DGL equality


# Problems to understand a stochastic DGL equality












currently I am reading a paper called "Portfolio optimisation under non-linear drawdown constraints in a semimartingale financial model" for self-study reasons. The paper can be found here: http://arxiv.org/abs/1110.6289

There, I found an equation I don't understand.

In Chapter 7 the authors are trying to calculate a wealth process.

The wealth process $X_t$ satisfies the following SDGL $$dX_t = (X_t - w(\bar{X_t}))\frac{dV_t}{V_t}, (1)$$ since in chaper 7 everthing is continuous.

The process $V_t$ satisfies the follwing equation $$dV_t=\pi_tdS_t := \sum{\pi_t^i}dS_t^i , (2) $$ for a preversibel $\pi_t$ and a d-dim semi-martingal $S_t$ with SDGL for every $i$ $$dS^i_t = S^i_t(\mu^i_t dt+\sum\sigma^{ij}_t dW^j_t) , $$ where $W_t = (W^1_t,\dots,W^d_t)$ is a d-dim Wiener process. Now the authors claim that by plugging $(2)$ in $(1)$ they obtain: $$dX_t = (X_t - w(\bar{X_t}))\sum\pi^i_t\frac{dS_t^i}{S^i_t} , (3) $$ where $\pi^i_t = (\frac{1}{1-\gamma(1-\alpha)}\theta'_i\sigma^{-1}_t)^i $. I think the exact form of $\pi_i$ shouldn't matter, only that it is preversible.

My question is: How do the authors came up with $(3)$? The way I'am doing it is: $$dX_t = (X_t - w(\bar{X_t}))\sum\pi^i_t\frac{dS_t^i}{V_t} .$$

Sadly, only $(3)$ seems to be consisting with the literature (one can find a similar solution for $(3)$ in "On Portfolio Optimization under "Drawdown" Constraints" http://www.math.columbia.edu/~ik/Drawdown.pdf) . What am I doing wrong?

## Answer by quasi (score 1, accepted)

https://quant.stackexchange.com/a/9601

I haven't read all the paper, just the section you mentioned. The previsible/predictable strategy $\pi_t$ represents the number of shares of the asset $S$ held at time $t$. The paper looks to use power utility in some way, and as is common in those types of problems, generally you want to think of $\tilde{\pi}_t$, which is the percentage of wealth at time $t$ held in the risky assets.

Towards the bottom of p. 21, you can see that they define $$ \tilde{\pi}_t := \pi_t S_t / V_t. $$

Using $\tilde{\pi}_t$ instead of $\pi_t$ solves your problem I believe. Also, equation (22) on p. 22 shows that the optimal $\tilde{\pi}$ has the form you describe above.

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