Correlation coefficient in finance 
An asset A has volatility estimated as σA = 0.2
An asset B has volatility estimated as σB = 0.4
The assets have covariance = σAB = -0.33
State the hypothesis of correlation and test this at a 10% significance level

So firstly I worked out the correlation coefficient which I believe to be -4.125 I did this by

p=$-0.33/(0.2*0.4)$
adding to this I am told by the teacher I need to revere engineer the formula for d using a value taken from the Normal table. However I’m even unsure what my normal table value is

 A: We can test the correlation using the fact that when the correlation is null then the statistic 
$$
t = r \sqrt{\frac{n-2}{1-r^2}}
$$
(where $r=\frac{\sigma_{AB}}{\sigma_A \sigma_B}$ is the sample correlation coefficient and $n$ is the sample size)
is approximately distributed as student's T with $n-2$ degrees of freedom if the samples are large enough.
You would need to plug in your value of $n$, and find the critical $t$ value that would give you the desired significance.
Then you could invert the formula as $r = - \frac{t}{\sqrt{n-2+t^2}}$, and if your estimated $r$ is below that threshold then the null hypothesis of no correlation would be falsified.
For example, if $n=42$ then the critical $t$ value for $n-2 = 40$ degrees of freedom and $10\%$ significance level would be $1.684$ according to this table. 
Thus the critical $r$ value would be $r = - \frac{t}{\sqrt{n-2+t^2}} = - \frac{1.684}{\sqrt{40+1.684^2}} = - 0.03931$. Since the estimated $r$-value is $r = -4.125 < - 0.03931$ we would reject the null hypothesis and confirm that the assets are negatively correlated.
