In (univariate) kernel density estimation, I often come across constructions where some Taylor expansion like
$ \int K_h ( u - y) f(y) dy = \int K(x) f( u - hx) dx = \sum_{k = 0}^2 h^{2k} f^{(2k)} (u) \frac{m_{2k}(K)}{(2k)!} + O(h^6)$
is done and then (may the following $O(h^6)$ represent the same term as above)
$ \int \int L_g(z) O(h^6) f(u + hz) dz du = m_0(L)O(h^6) + m_2(L) O(g^2 h^6) + O(g^4 h^6), $
where $L, K$ are bounded symmetric kernels with finite moments $m_1, ... m_8$ and bandwidths $h,g$. Furthermore $ \text{sup}_{x \in \mathbb R} | f^{(j)}(x) < \infty $ for $j = 1, ..., 6$. My question is, why the $O(h^6)$ remains under integration? Couldn't it be possible that even if the kernels are bounded, they have some infinite higher moments or that terms like $\int f^{(k)} O(h^6)$ for big $k$ are infinite? Or do I need some further conditions?