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Let me try an answer. [Edit: simplified and (hopefully) corrected.]

Let $\alpha$ be the only positive solution of $\mathrm{ch}\alpha = \exp(\varepsilon\alpha)$, so that $$ \exp(\alpha x) = \frac12\left(\exp(\alpha(x+1-\varepsilon))+\exp(\alpha(x - 1 - \varepsilon))\right)\text. $$ The purpose of the definition lies in the fact that $\mathbb E[\mathbf e^{\alpha|X^{(n+1)}|}|\mathcal F_n]=\mathbf e^{\alpha|X^{(n)}|}$ whenever $|X^{(n)}|\geq 1+\varepsilon$. I claim that:

For $C>0$ large enough, $$\mathbf e^{\alpha|X^{(n)}|}-Cn$$ is a supermartingale.

Indeed, because of the remark above, it is enough to show that for some constant $C>0$, $$\mathbb E[\mathbf e^{\alpha|X^{(n+1)}|}|\mathcal F_n]\leq \mathbf e^{\alpha|X^{(n)}|} + C$$ whenever $|X^{(n)}|< 1+\varepsilon$. This is true for $C=\max\{\mathbf e^{\alpha x},0\leq x\leq 2\}=\mathbf e^{2\alpha}$, for example.

This means that $\mathbb E[\mathbf e^{\alpha |X^{(n)}|}]\leq 1+Cn$, so $X^{(n)}$ cannot explode that much. For example, about the variance, for any positive exponent $p\in\mathbb N$, $$ \mathbb E[|X^{(n)}|^2] \leq \mathbb E[|X^{(n)}|^{2p}]^{1/p} \leq K\mathbb E[\mathbf e^{\alpha|X^{(n)}|}]^{1/p} \leq K'(1+n)^{1/p}\text,$$ so the variance increases slower that any root.

As Martin pointed out below (thank you!), $\mathbb E[\exp(a|X^{(n)}|)]\leq C'$ whenever $a<\alpha$. It can be seen as a consequence of the modified claim:

For $C\geq1$ large enough and $\lambda=\mathrm{ch}(a)\exp(-\varepsilon a)$, $$\mathbb E[\mathbf e^{a|X^{(n+1)}|}|\mathcal F_n]\leq \lambda\mathbf e^{a|X^{(n)}|} + C\text.$$

When $X^{(n)}\geq 1+\varepsilon$, this is a consequence of \begin{align*} \mathbb E[\mathbf e^{a|X^{(n+1)}|}|\mathcal F_n] = & \frac12\left(\exp(a(X^{(n)}+1-\varepsilon))+\exp(a(X^{(n)} - 1 - \varepsilon))\right)\\ = & \mathbf e^{a|X^{(n)}|}\mathrm{ch}(a)\exp(\varepsilon a)\text, \end{align*} and similarly when $X^{(n)}\leq -1-\varepsilon$; when $|X^{(n)}|<1+\varepsilon$, $$\mathbb E[\mathbf e^{a|X^{(n+1)}|}|\mathcal F_n]\leq\mathbf e^{2a}\text,$$ and the claim follows.

From the claim, and noting that $\lambda<1$, we see that $$ \mathbb E[\mathbf e^{a|X^{(n)}|}|] \leq C(1+\lambda+\cdots+\lambda^n) \leq \frac C{1-\lambda}$$ so $\mathbb E[\exp(a|X^{(n)}|)]$ (hence the variance) is uniformly bounded.

Let me try an answer. [Edit: simplified and (hopefully) corrected.]

Let $\alpha$ be the only positive solution of $\mathrm{ch}\alpha = \exp(\varepsilon\alpha)$, so that $$ \exp(\alpha x) = \frac12\left(\exp(\alpha(x+1-\varepsilon))+\exp(\alpha(x - 1 - \varepsilon))\right)\text. $$ The purpose of the definition lies in the fact that $\mathbb E[\mathbf e^{\alpha|X^{(n+1)}|}|\mathcal F_n]=\mathbf e^{\alpha|X^{(n)}|}$ whenever $|X^{(n)}|\geq 1+\varepsilon$. I claim that:

For $C>0$ large enough, $$\mathbf e^{\alpha|X^{(n)}|}-Cn$$ is a supermartingale.

Indeed, because of the remark above, it is enough to show that for some constant $C>0$, $$\mathbb E[\mathbf e^{\alpha|X^{(n+1)}|}|\mathcal F_n]\leq \mathbf e^{\alpha|X^{(n)}|} + C$$ whenever $|X^{(n)}|< 1+\varepsilon$. This is true for $C=\max\{\mathbf e^{\alpha x},0\leq x\leq 2\}=\mathbf e^{2\alpha}$, for example.

This means that $\mathbb E[\mathbf e^{\alpha |X^{(n)}|}]\leq 1+Cn$, so $X^{(n)}$ cannot explode that much. For example, about the variance, for any positive exponent $p\in\mathbb N$, $$ \mathbb E[|X^{(n)}|^2] \leq \mathbb E[|X^{(n)}|^{2p}]^{1/p} \leq K\mathbb E[\mathbf e^{\alpha|X^{(n)}|}]^{1/p} \leq K'(1+n)^{1/p}\text,$$ so the variance increases slower that any root.

As Martin pointed out below (thank you!), $\mathbb E[\exp(a|X^{(n)}|)]\leq C'$ whenever $a<\alpha$. It can be seen as a consequence of the modified claim:

For $C\geq1$ large enough and $\lambda=\mathrm{ch}(a)\exp(-\varepsilon a)$, $$\mathbb E[\mathbf e^{a|X^{(n+1)}|}|\mathcal F_n]\leq \lambda\mathbf e^{a|X^{(n)}|} + C\text.$$

When $X^{(n)}\geq 1+\varepsilon$, this is a consequence of \begin{align*} \mathbb E[\mathbf e^{a|X^{(n+1)}|}|\mathcal F_n] = & \frac12\left(\exp(a(X^{(n)}+1-\varepsilon))+\exp(a(X^{(n)} - 1 - \varepsilon))\right)\\ = & \mathbf e^{a|X^{(n)}|}\mathrm{ch}(a)\exp(-\varepsilon a)\text, \end{align*} and similarly when $X^{(n)}\leq -1-\varepsilon$; when $|X^{(n)}|<1+\varepsilon$, $$\mathbb E[\mathbf e^{a|X^{(n+1)}|}|\mathcal F_n]\leq\mathbf e^{2a}\text,$$ and the claim follows.

From the claim, and noting that $\lambda<1$, we see that $$ \mathbb E[\mathbf e^{a|X^{(n)}|}|] \leq C(1+\lambda+\cdots+\lambda^n) \leq \frac C{1-\lambda}$$ so $\mathbb E[\exp(a|X^{(n)}|)]$ (hence the variance) is uniformly bounded.

Let me try an answer. [Edit: simplified and (hopefully) corrected.]

Let $\alpha$ be the only positive solution of $\mathrm{ch}\alpha = \exp(\varepsilon\alpha)$, so that $$ \exp(\alpha x) = \frac12\left(\exp(\alpha(x+1-\varepsilon))+\exp(\alpha(x - 1 - \varepsilon))\right)\text. $$ The purpose of the definition lies in the fact that $\mathbb E[\mathbf e^{\alpha|X^{(n+1)}|}|\mathcal F_n]=\mathbf e^{\alpha|X^{(n)}|}$ whenever $|X^{(n)}|\geq 1+\varepsilon$. I claim that:

For $C>0$ large enough, $$\mathbf e^{\alpha|X^{(n)}|}-Cn$$ is a supermartingale.

Indeed, because of the remark above, it is enough to show that for some constant $C>0$, $$\mathbb E[\mathbf e^{\alpha|X^{(n+1)}|}|\mathcal F_n]\leq \mathbf e^{\alpha|X^{(n)}|} + C$$ whenever $|X^{(n)}|< 1+\varepsilon$. This is true for $C=\max\{\mathbf e^{\alpha x},0\leq x\leq 2\}=\mathbf e^{2\alpha}$, for example.

This means that $\mathbb E[\mathbf e^{\alpha |X^{(n)}|}]\leq 1+Cn$, so $X^{(n)}$ cannot explode that much. For example, about the variance, for any positive exponent $p\in\mathbb N$, $$ \mathbb E[|X^{(n)}|^2] \leq \mathbb E[|X^{(n)}|^{2p}]^{1/p} \leq K\mathbb E[\mathbf e^{\alpha|X^{(n)}|}]^{1/p} \leq K'(1+n)^{1/p}\text,$$ so the variance increases slower that any root.

Let me try an answer. [Edit: simplified and (hopefully) corrected.]

Let $\alpha$ be the only positive solution of $\mathrm{ch}\alpha = \exp(\varepsilon\alpha)$, so that $$ \exp(\alpha x) = \frac12\left(\exp(\alpha(x+1-\varepsilon))+\exp(\alpha(x - 1 - \varepsilon))\right)\text. $$ The purpose of the definition lies in the fact that $\mathbb E[\mathbf e^{\alpha|X^{(n+1)}|}|\mathcal F_n]=\mathbf e^{\alpha|X^{(n)}|}$ whenever $|X^{(n)}|\geq 1+\varepsilon$. I claim that:

For $C>0$ large enough, $$\mathbf e^{\alpha|X^{(n)}|}-Cn$$ is a supermartingale.

Indeed, because of the remark above, it is enough to show that for some constant $C>0$, $$\mathbb E[\mathbf e^{\alpha|X^{(n+1)}|}|\mathcal F_n]\leq \mathbf e^{\alpha|X^{(n)}|} + C$$ whenever $|X^{(n)}|< 1+\varepsilon$. This is true for $C=\max\{\mathbf e^{\alpha x},0\leq x\leq 2\}=\mathbf e^{2\alpha}$, for example.

This means that $\mathbb E[\mathbf e^{\alpha |X^{(n)}|}]\leq 1+Cn$, so $X^{(n)}$ cannot explode that much. For example, about the variance, for any positive exponent $p\in\mathbb N$, $$ \mathbb E[|X^{(n)}|^2] \leq \mathbb E[|X^{(n)}|^{2p}]^{1/p} \leq K\mathbb E[\mathbf e^{\alpha|X^{(n)}|}]^{1/p} \leq K'(1+n)^{1/p}\text,$$ so the variance increases slower that any root.

As Martin pointed out below (thank you!), $\mathbb E[\exp(a|X^{(n)}|)]\leq C'$ whenever $a<\alpha$. It can be seen as a consequence of the modified claim:

For $C\geq1$ large enough and $\lambda=\mathrm{ch}(a)\exp(-\varepsilon a)$, $$\mathbb E[\mathbf e^{a|X^{(n+1)}|}|\mathcal F_n]\leq \lambda\mathbf e^{a|X^{(n)}|} + C\text.$$

When $X^{(n)}\geq 1+\varepsilon$, this is a consequence of \begin{align*} \mathbb E[\mathbf e^{a|X^{(n+1)}|}|\mathcal F_n] = & \frac12\left(\exp(a(X^{(n)}+1-\varepsilon))+\exp(a(X^{(n)} - 1 - \varepsilon))\right)\\ = & \mathbf e^{a|X^{(n)}|}\mathrm{ch}(a)\exp(\varepsilon a)\text, \end{align*} and similarly when $X^{(n)}\leq -1-\varepsilon$; when $|X^{(n)}|<1+\varepsilon$, $$\mathbb E[\mathbf e^{a|X^{(n+1)}|}|\mathcal F_n]\leq\mathbf e^{2a}\text,$$ and the claim follows.

From the claim, and noting that $\lambda<1$, we see that $$ \mathbb E[\mathbf e^{a|X^{(n)}|}|] \leq C(1+\lambda+\cdots+\lambda^n) \leq \frac C{1-\lambda}$$ so $\mathbb E[\exp(a|X^{(n)}|)]$ (hence the variance) is uniformly bounded.

Let me try an answer. [Edit: simplified]

Let $\alpha$ be the only positive solution of $\mathrm{ch}\alpha = \exp(\varepsilon\alpha)$, so that $$ \exp(\alpha x) = \frac12\left(\exp(\alpha(x+1-\varepsilon))+\exp(\alpha(x - 1 - \varepsilon))\right)\text. $$ The purpose of the definition lies in the fact that $\mathbb E[\mathbf e^{\alpha|X^{(n+1)}|}|\mathcal F_n]=\mathbf e^{\alpha|X^{(n)}|}$ whenever $|X^{(n)}|\geq 1+\varepsilon$. I claim that:

For $C>0$ large enough, $$\mathbf e^{\alpha|X^{(n)}|}-Cn-1$$ is a supermartingale.

Indeed, because of the remark above, it is enough to show that for some constant $C>0$, $$\mathbb E[\mathbf e^{\alpha|X^{(n+1)}|}|\mathcal F_n]\leq \mathbf e^{\alpha|X^{(n)}|} + C$$ whenever $|X^{(n)}|< 1+\varepsilon$. This is true for $C=\max\{\mathbf e^{\alpha x},0\leq x\leq 2\}$, for example.

This means that $\mathbb E[\mathbf e^{\alpha |X^{(n)}|}]\leq Cn$, so $X^{(n)}$ cannot explode that much. For example, about the variance, for any positive exponent $p\in\mathbb N$, $$ \mathbb E[|X^{(n)}|^2] \leq \mathbb E[|X^{(n)}|^{2p}]^{1/p} \leq K\mathbb E[\mathbf e^{\alpha|X^{(n)}|}]^{1/p} \leq K'n^{1/p}\text,$$ so the variance increases slower that any root.

Let me try an answer. [Edit: simplified and (hopefully) corrected.]

Let $\alpha$ be the only positive solution of $\mathrm{ch}\alpha = \exp(\varepsilon\alpha)$, so that $$ \exp(\alpha x) = \frac12\left(\exp(\alpha(x+1-\varepsilon))+\exp(\alpha(x - 1 - \varepsilon))\right)\text. $$ The purpose of the definition lies in the fact that $\mathbb E[\mathbf e^{\alpha|X^{(n+1)}|}|\mathcal F_n]=\mathbf e^{\alpha|X^{(n)}|}$ whenever $|X^{(n)}|\geq 1+\varepsilon$. I claim that:

For $C>0$ large enough, $$\mathbf e^{\alpha|X^{(n)}|}-Cn$$ is a supermartingale.

Indeed, because of the remark above, it is enough to show that for some constant $C>0$, $$\mathbb E[\mathbf e^{\alpha|X^{(n+1)}|}|\mathcal F_n]\leq \mathbf e^{\alpha|X^{(n)}|} + C$$ whenever $|X^{(n)}|< 1+\varepsilon$. This is true for $C=\max\{\mathbf e^{\alpha x},0\leq x\leq 2\}=\mathbf e^{2\alpha}$, for example.

This means that $\mathbb E[\mathbf e^{\alpha |X^{(n)}|}]\leq 1+Cn$, so $X^{(n)}$ cannot explode that much. For example, about the variance, for any positive exponent $p\in\mathbb N$, $$ \mathbb E[|X^{(n)}|^2] \leq \mathbb E[|X^{(n)}|^{2p}]^{1/p} \leq K\mathbb E[\mathbf e^{\alpha|X^{(n)}|}]^{1/p} \leq K'(1+n)^{1/p}\text,$$ so the variance increases slower that any root.